CA2516553C - Use of intronic rna to measure gene expression - Google Patents

Use of intronic rna to measure gene expression Download PDF

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CA2516553C
CA2516553C CA2516553A CA2516553A CA2516553C CA 2516553 C CA2516553 C CA 2516553C CA 2516553 A CA2516553 A CA 2516553A CA 2516553 A CA2516553 A CA 2516553A CA 2516553 C CA2516553 C CA 2516553C
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Randal W. Scott
Michael C. Kiefer
Joffre B. Baker
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Genomic Health Inc
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Abstract

The invention is based on the use of intronic RNA in monitoring gene expression. Accordingly, the present invention concerns methods of gene expression profiling using intronic RNA, the expression of which correlates with the expression of corresponding exonic RNA, and diagnostic and prognostic methods based on the results of such gene expression studies.

Description

USE OF INTRONIC RNA TO MEASURE GENE EXPRESSION
Background of the Invention Field of the Invention It is well recognized that gene expression within cells and tissues can indicate the physiologic and or pathologic status of the cell, tissue or patient. For several decades, gene expression, as measured by immunohistochemical analysis of protein markers, has been used to make treatment decisions. For example, levels of estrogen receptor and progesterone receptor measured this way are now routinely used to select breast cancer patients for treatment with anti-estrogen drugs.

More recent research literature provides evidence that tissue levels of mRNA
species have diagnostic and prognostic value. This is a promising development because the technologies for measurement of cellular RNA levels, as exemplified by multiple RT-PCR
and DNA array platforms, can be very sensitive, specific and quantitative. RT-PCR is recognized as generally more sensitive than DNA array technology. However, RT-PCR
probe/primer design and selection can be challenging, because multiple criteria exist for optimal performance. This challenge is particularly great when the sample RNA
to be studied comes from fixed, wax-embedded tissue, because such RNA tends to be highly fragmented (K.Specht et al., Ana. J. hat/wi 158: 419-29 [2001]; T.E. Godfrey et al., J. M
l. Diagnostics 2:84-91 [2000]).

It is accepted practice to measure the expression of any given gene by assaying the level of any of its transcribed, spliced, mature mRNA sequences (exon, as opposed to intron, sequence). hi theory, an exon is defined as any segment of an interrupted gene that is represented in the mature RNA product, and an intron is defined as a segment of DNA that is transcribed but removed from within the transcript by splicing together the exons on either side of it [B. Lewin. Genes IV, Cell Press, Cambridge Mass. 1990]. The rationale for the accepted practice of using exon sequences is theoretically straightforward because the mature RNAs [mRNAs] encode proteins, which define cell phenotypes, whereas intronic RNA is considered to have comparatively little influence on cell phenotype. Moreover, the prevailing view is that introns are rapidly degraded and therefore more difficult to detect than exon sequences {see introductions of the following articles: Thomas et al., J.
Virol. 76:532-40 [2002]; Clement et al., J. Biol. Chem. 276:16919-30 [2001]; Sharp et al., Ann.
Rev. Biochem.
55:1119-1150 [1986]}.
The present invention concerns the use of intronic RNA for measuring gene expression. It will be shown that intronic RNA sequences tend to be readily detected by RT-PCR, even using extensively degraded RNA from fixed tissues. Furthermore, they tend to correlate in their expression with their respective exons. The latter point is particularly unexpected because little or no evidence exists that the ratio of the overall rate constants for synthesis and turnover of transcribed intron and exon sequences are similar.
In fact, the scientific literature provides evidence for the complexity of pre-mRNA and spliced intron turnover. For example, pre-mRNA can exist in multiple kinetic pools (Elliott and Rosbash, Exp. Cell Res. 229:181-8 [1996]), with subpopulations containing intron RNAs that are not efficiently spliced out and are transported to the cytoplasm as "immature"
mRNA species, where they can decay at rates different than nuclear intron RNA sequences (Wang et al., Proc.
Natl. Acad. Sci. USA 94:4360-5 [1997]). Furthermore, certain spliced intron RNAs seem to enter the cytoplasm in lariat structure (Clement et al., RNA 5:206-20 [1999]).

Summary of the Invention The present invention is based on experimental evidence demonstrating that transcribed intron sequences, which by definition are present in heterogeneous nuclear RNA
but typically are not incorporated into mRNA, have diagnostic and prognostic utility. This is a significant discovery for several reasons. Typically, intron sequences are longer than exon sequences, by twenty fold or more. Thus, introns, given their much greater average length, provide proportionally increased opportunity for optimal gene expression probe design, for example, in the case of RT-PCR, creation of probe/primer sets that possess better technical performance. Independently, because intron sequences evolve more rapidly than exon sequences, intronic RNAs are well-suited to monitor the expression of different closely related members of a gene family.
In one aspect, the invention concerns a method for monitoring gene expression in a biological sample, comprising:
(a) providing a polynucleotide complementary to an intronic RNA sequence within a target gene, wherein the expression of such intronic RNA sequence correlates with the expression of an exonic mRNA sequence within the target gene;

(b) hybridizing the polynucleotide to the intronic RNA sequence to form a polynucleotide-intronic RNA complex; and (c) detecting the polynucleotide-intronic RNA complex.
In a particular aspect, expression of the target gene is measured by RT-PCR, in which case an intron-based primer/probe set can be used in the above process.
In another aspect, the invention concerns methods of using intron-based sequences to design and create primer-probe sets for RT-PCR. Such primers and probes are particularly suitable to detect and quantify levels of intron RNA in fixed, paraffin-embedded tissue (FPET) specimens, for high sensitivity gene expression analysis. Accordingly, in a further aspect, the invention concerns using intron-based primer-probe sets in gene expression profiling assays, such as gene expression analysis of FPET samples to diagnose and/or predict the prognosis of various pathologic conditions.
In particular, the invention concerns a method of preparing a single-stranded oligonucleotide molecule for amplification of a target gene, and measuring the level of an intronic RNA species comprising:
(a) identifying at least one intron sequence within the target gene, wherein the expression of the intron sequence correlates with the expression of an exon sequence within the target gene;
(b) preparing a single-stranded oligonucleotide molecule that corresponds to at least a portion of the transcribed intron sequence; and (c) using the oligonucleotide molecule to measure gene expression.

Just as before, gene expression can be measured, for example, by RT-PCR, in which case an intron-based primer/probe set (consisting of two primers and a probe) is used to measure gene expression.
If the oligonucleotide is a forward primer, it is typically designed to comprise 5'-sequences of a target sequence within the transcribed intron sequence. If the oligonucleotide is a reverse primer, it is typically designed to complement 5'-sequences of a target sequence downstream of the forward primer within the transcribed intron sequence. It is important to identify and use a sufficiently long target sequence for PCR amplification.
The target sequence generally should be at least about 50 nucleotide bases long, in particular at least 55 nucleotide bases long, in some embodiments at least about 60 nucleotide bases long. The PCR primers and probes are designed following well known principles. Thus, the PCR
primer is typically 17-30 nucleotide bases in length, and usually contains about 20% to 80%
G+C bases. It is desirable to design PCR primers with a melting temperature (Tm) between about 50 C and about 70 C.
When the single-stranded oligonucleotide molecule is a PCR probe, it is usually designed to comprise or complement an internal portion of a target sequence within the transcribed intron sequence. For TagMan amplification, the PCR probe is labeled with a reporter fluorescent dye and a quencher moiety.

In another aspect, the invention concerns a method for measuring the expression of a gene by amplifying a target gene by polymerase chain reaction (PCR) comprising:

(a) identifying at least one target intron sequence within the target gene, wherein the expression of the intron sequence correlates with the expression of a corresponding exon sequence within the target gene; and (b) amplifying the transcribed target intron sequence using an intron-specific PCR primer/probe set.
The target intron sequence is typically at least about 50 bases long, and the PCR
primer and probe set is designed to correspond to unique sequences within the transcribed target intron sequence.
In yet another aspect, the invention concerns a method for amplifying RNA
fragments in a sample representing at least one gene of interest, comprising the steps of:
(a) contacting the sample with at least one set of PCR primers and probe; and (b) performing PCR amplification, wherein the PCR primers and probe are designed based upon an intron sequence identified within the gene of interest, and wherein the expression of the intron sequence correlates with the expression of an exon sequence within the gene of interest.

In particular embodiment, the PCR primers and probe are typically designed based upon a unique sequence within the intron identified. In another embodiment, the sample comprises fragmented RNA representing multiple genes of interest, and is contacted with a pool of PCR primers and probes designed based upon unique sequences within introns present in the genes of interest.
In a preferred embodiment, the amplification is performed on a fixed, paraffin-embedded tissue (FPET) sample, which can, for example, originate from a tumor biopsy obtained from a human patient. The tumor can be any kind of solid tumor, such as, for example, breast cancer, lung cancer, or colorectal cancer. The tumor tissue can be harvested by a variety of methods, including fine needle biopsy, core biopsy or resection.
In a particular embodiment, the invention concerns methods using intron-based PCR
primer-probe sets in gene expression analysis to predict the likelihood of recurrent disease for patients with early breast cancer.
In a further aspect, the invention concerns an array comprising a plurality of polynucleotides hybridizing to target genes of interest, wherein preferably at least 70% of the polynucleotides comprises intron sequences.
In yet another aspect, the invention concerns intron-based amplicon sequences, and their use in gene expression analysis.
In a particular embodiment the invention concerns gene expression analysis of a biological sample representative of invasive breast cancer based on determining the expression levels of the RNA transcripts or expression products of a gene or gene set selected from the group consisting of.
(a) Bc12, cyclinGl, NFKBp65, NME1, EPHX1, TOP2B, DR5, TERC, Src, DIABLO;
(b) Ki67, XIAP, hENT1, TS, CD9, p27, cyclinGl, pS2, NFKBp65, CYP3A4;
(c) GSTM1, XIAP, Ki67, TS, cyclinGl, p27, CYP3A4, pS2, NFKBp65, ErbB3;
(d) PR, NME1, XIAP, upa, cyclinGl, Contig51037, TERC, EPHX1, ALDHIA3, CTSL;
(e) CA9, NME1, TERC, cyclinGl, EPHXI, DPYD, Src, TOP2B, NFKBp65, VEGFC;
(f) TFRC, XIAP, Ki67, TS, cyclinGl, p27, CYP3A4, pS2, ErbB3, NFKBp65;
(g) Bc12, PRAME, cyclinGl, FOXM1, NFKBp65, TS, XIAP, Ki67, CYP3A4, p27;
(h) FOXM1, cyclinGl, XIAP, Contig51037, PRAME, TS, Ki67, PDGFRa, p27, NFKBp65;
(i) PRAME, FOXM1, cyclinGl, XIAP, Contig51037, TS, Ki6, PDGFRa, p27, NFKBp65;
(j) Ki67, XIAP, PRAME, hENT1, contig51037, TS, CD9, p27, ErbB3, cyclinGl;
(k) STK15, XIAP, PRAME, PLAUR, p27, CTSL, CD18, PREP, p53, RPS6KB1;
(1) GSTM1, XIAP, PRAME, p27, Contig51037, ErbB3, GSTp, EREG, ID1, PLAUR;
(m) PR, PRAME, NME1, XIAP, PLAUR, cyclinGl, Contig51037, TERC, EPHX1, DR5;
(n) CA9, FOXM1, cyclinGl, XIAP, TS, Ki67, NFKBp65, CYP3A4, GSTM3, p27;
(o) TFRC, XIAP, PRAME, p27, Contig51037, ErbB3, DPYD, TERC, NME1, VEGFC; and (p) CEGP1, PRAME, hENT1, XIAP, Contig51037, ErbB3, DPYD, NFKBp65, ID1, TS, including the use of intron-based sequences.
In another embodiment, the invention concerns gene expression analysis of a biological sample representative of ER-positive breast cancer based on determining the expression levels of the RNA transcripts or expression products of a gene or gene set selected from the group consisting of:

(a) PRAME, p27, IGFBP2, H1F1A, TIMP2, ILT2, CYP3A4, ID1, EstRl, DIABLO;
(b) Contig51037, EPHX1, Ki67, TIMP2, cyclinGl, DPYD, CYP3A4, TP, AIB1, CYP2C8;
(c) Bc12, hENT1, FOXM1, Contig51037, cyclinGl, Contig46653, PTEN, CYP3A4, TIMP2, AREG;
(d) HIFIA, PR.AME, p27, IGFBP2, TIIAP2, ILT2, CYP3A4, ID1, EstRl, DIABLO;
(e) IGF1R, PRAME, EPHX1, Contig51037, cyclinGl, Bc12, NME1, PTEN, TBP, TIMP2;
(f) FOXM1, Contig51037, VEGFC, TBP, HIF1A, DPYD, RAD51C, DCR3, cyclinGl, BAG1;
(g) EPHX1, Contig51037, Ki67, TIMP2, cyclinGl, DPYD, CYP3A4, TP, AIB1, CYP2C8;
(h) Ki67, VEGFC, VDR, GSTM3, p27, upa, ITGA7, rhoC, TERC, Pinl;
(i) CDC25B, Contig51037, hENT1, Bc12, HLAG, TERC, NME1, upa, ID1, CYP;
(j) VEGFC, Ki67, VDR, GSTM3, p27, upa, ITGA7, rhoC, TERC, Pinl;

(k) CTSB, PRAME, p27, IGFBP2, EPHX1, CTSL, BAD, DR5, DCR3, XIAP;
(1) DIABLO, Ki67, hENT1, TIMP2, ID1, p27, KRT19, IGFBP2, TS, PDGFB;
(m) p27, PRAME, IGFBP2, HIF1A, TIMP2, ILT2, CYP3A4, ID1, EstRl, DIABLO;
(n) CDHl; PRAME, VEGFC; HIF1A; DPYD, TIVIP2, CYP3A4, EstRl, RBP4, p27;
(o) IGFBP3, PRAME, p27, Bc12, XIAP, EstRl, Ki67, TS, Src, VEGF;

(p) GSTM3, PRAME, p27, IGFBP3, XIAP, FGF2, hENT1, PTEN, EstRl, APC;
(q) hENT1, Bc12, FOXM1, Contig51037, CyclinGl, Contig46653, PTEN, CYP3A4, TIMP2, AREG;
(r) STK15, VEGFC, PRAME, p27, GCLC, hENT1, ID 1, TIMP2, EstRl, MCP1;
(s) NME1, PRAM, p27, IGFBP3, XIAP, PTEN, hENT1, Bc12, CYP3A4, HLAG;
(t) VDR, Bc12, p27, hENT1, p53, PI3KC2A, EIF4E, TFRC, MCM3, IDl;

(u) EIF4E, Contig51037, EPHX1, cyclinGl, Bc12, DR5, TBP, PTEN, NME1, HER2;
(v) CCNB1, PRAME, VEGFC, HIF1A, hENT1, GCLC, TIMP2, ID1, p27, upa;
(w) ID1, PRAME, DIABLO, hENT1, p27, PDGFRa, NME1, BIN1, BRCA1, TP;
(x). FBXO5, PRAME, IGFBP3, p27, GSTM3, hENT1, XIAP, FGF2, TS, PTEN;
(y) GUS, HIA1A, VEGFC, GSTM3, DPYD, hENT1, EBXO5, CA9, CYP, KRT18; and (z) Bclx, Bc12, hENT1, Contig51037, HLAG, CD9, ID1, BRCA1, BIN1, HBEGF, including the use of intron-based sequences.
In a further embodiment, the cancer is breast cancer, and the gene(s) analyzed is/are selected from the group consisting of. FOXMI; PRA ME; SKT15, Ki-67; CA9; NME1;
SURV; TFRC; YB-1; RPS6KB1; Src; Chkl; CCNB1; Chk2; CDC25B; CYP3A4; EpCAi4;

VEGFC; hENT1; BRCA2; EGFR; TK1; VDR; Blcl2; CEGP1; GSTM1; PR; BBC3;
GATA3; DPYD; GSTM3; IDl; EstRl; p27; XIAP; IGF1R; AK055699; P13KC2A; TGFB3;
BAGI1; pS2; WISP1; HNF3A; and NFKBp65.
In a still further embodiment, invention concerns gene expression analysis of a biological sample representative of invasive breast cancer, based on determining the expression levels of the RNA transcripts or expression products of a gene or gene set selected from the group consisting of (a) p53BP2, Bcl2, BAD, EPHX1, PDGFR(3, DIABLO, XIAP, YB1, CA9, and KRT8;
(b) GRB7, CD68, TOP2A, Bc12, DIABLO, CD3, ID1, PPM1D, MCM6, and WISP1;
(c) PR, p53BP2, PRAME, DIABLO, CTSL, IGFBP2, TIMP1, CA9, MMP9, and COX2;
(d) CD68, GRB7, TOP2A, Bc12, DIABLO, CD3, ID1, PPM1D, MCM6, and WISP1;
(e) Bc12, p53BP2, BAD, EPHX1, PDGFR(3, DIABLO, XIAP, YB1, CA9, and KRT8;
(f) KRT14, KRT5, PRAME, p53BP2, GUS1, AIB1, MCM3, CCNE1, MCM6, and IDl;
(g) PRAME, p53BP2, EstRl, DIABLO, CTSL, PPM1D, GRB7, DAPK1, BBC3, and VEGFB;
(h) CTSL2, GRB7, TOP2A, CCNB1, Bc12, DIABLO, PRAME, EMS1, CA9, and EpCAM;
(i) EstRl, p53BP2, PRAME, DIABLO, CTSL, PPM1D, GRB7, DAPK1, BBC3, and VEGFB;
(j) Chkl, PRAME, p53BP2, GRB7, CA9, CTSL, CCNB1, TOP2A, tumor size, and IGFBP2;
(k) IGFBP2, GRB7, PRAME, DIABLO, CTSL, (3-Catenin, PPM1D, Chkl, WISP1, and LOT1;
(1) HER2, p53BP2, Bc12, DIABLO, TIMP1, EPHX1, TOP2A, TRAIL, CA9, and AREG;
(m) BAG1, p53BP2, PRAME, IL6, CCNB1, PAIL, AREG, tumor size, CA9, and Ki67;
(n) CEGP1, p53BP2, PRAME, DIABLO, Bc12, COX2, CCNE1, STK15, and AKT2, and FGF 18;
(0) STK15, p53BP2, PRAME, IL6, CCNE1, AKT2, DIABLO, cMet, CCNE2, and COX2;
(p) KLK10, EstRl, p53BP2, PRAMS, DIABLO, CTSL, PPM1D, GRB7, DAPK1, and BBC3;
(q) AIB1, p53BP2, Bc12, DIABLO, TIMP1, CD3, p53, CA9, GRB7, and EPHX1 (r) BBC3, GRB7, CD68, PRAME, TOP2A, CCNB1, EPHXI, CTSL

GSTM1, and APC;
(s) CD9, GRB7, CD68, TOP2A, Bc12, CCNB1, CD3, DIABLO, ID1, and PPM1D;
(t) EGFR, KRT14, GRB7, TOP2A, CCNB1, CTSL, Bc12, TP, KLK10, and CA9;
(u) HIFlcx PR, DIABLO, PRAME, Chkl, AKT2, GRB7, CCNE1, TOP2A, and CCNB1;
(v) MDM2, p53BP2, DIABLO, Bc12, AIB1, TIMP1, CD3, p53, CA9, and HER2;
(w) MYBL2, p53BP2, PRAME, IL6, Bc12, DIABLO, CCNE1, EPHX1, TEMPI, and CA9;
(x) p27, p53BP2, PRAME, DIABLO, Bc12, COX2, CCNE1, STK15, AKT2, and ID1;

(y) RAD51, GRB7, CD68, TOP2A, CIAP2, CCNB1, BAG1, IL6, FGFR1, and p53BP2;
(z) SURV, GRB7, TOP2A, PRAME, CTSL, GSTM1, CCNB1, VDR, CA9; and CCNE2;
(aa) TOP2B, p53BP2, DIABLO, Bc12, TEMPI, AIB1, CA9, p53, KRT8, and BAD;
(ab) ZNF217, GRB7, p53BP2, PRAME, DIABLO, Bc12, COX2, CCNE1, APC4, and (3-Catenin.
In a different embodiment, the invention concerns gene expression analysis of a biological sample, using intron-based polynucleotide sequences hybridizing to at least one genes selected from the group consisting of: CD68; CTSL; FBXO5; SURV; CCNB1;
MCM2;
Chkl; MYBL2; HIF1A; cMET; EGFR; TS; STK15, IGFR1; BC12; HNF3A; TP53BP2;
GATA3; BBC3; RAD51C; BAG1; IGFBP2; PR; CD9; RB1; EPHX1; CEGPl; TRAIL; DR5;
p27; p53; MTA; RIZ1; ErbB3; TOP2B; EIF4E, CD68; CTSL; FBXO5; SURV; CCNB1;
MCM2; Chkl; MYBL2; HIF1A; cMET; EGFR; TS; and STK15.

Gene expression analysis may be performed in an array format, and the array preferably is a high-density array, comprising at least 100, more preferably at least 150, even more preferably, 200 sequences in a 5-10 section.

Brief Description of the Drawings Figures 1A-M show masked intron sequences for the CEGP1, FOXM1, PRAME, and STK15 genes. Amplicons used for RT-PCR are shown in italics.
Figure 2 shows primer/probe sets for CEGP1, FOXM1, PRAME, and STK15.
Sequences of forward and reverse primers are indicated by "F" and "R,"
respectively.
Sequences of primers are designated with "P."

Figure 3 shows correlation coefficients [R] for co-expression of CEGP1 exon RNA
with 47 other RNA sequences. Symbols: diamond = CEGP1 exon self vs. self (=1.0 by definition); squares=CEGP1 introns; triangles = sequences of other genes.

Figure 4 shows correlation coefficients [R] for co-expression of PRAME exon RNA
with 47 other RNA. sequences. Symbols: diamond - PRAISE exon self vs. self (=1.0 by definition); squares=PRAME introns; triangles = sequences of other genes.

Figure 5 shows correlation coefficients [R] for co-expression of STK15 exon RNA
with 47 other RNA sequences. Symbols: diamond - STK15 exon self vs. self (=1.0 by definition); squares=STK1 5 introns; triangles = sequences of other genes.
Figure 6 shows an exemplary set of genes, the expression of which can be analyzed by the methods of the present invention.

Detailed Description of the Preferred Embodiment A. Definitions Unless defined otherwise, technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Singleton et al., Dictionary of Microbiology and Molecular Biology 2nd ed., J.
Wiley & Sons (New York, NY 1994), provide one skilled in the art with a general guide to many of the terms used in the present application.
One skilled in the art will recognize many methods and materials similar or equivalent to those described herein, which could be used in the practice of the present invention.
Indeed, the present invention is in no way limited to the methods and materials described. For purposes of the present invention, the following terms are defined below.

The terms "splicing" and "RNA splicing" are used interchangeably and refer to RNA
processing that removes introns and joins exons to produce mature mRNA with continuous coding sequence that moves into the cytoplasm of an eukaryotic cell.

In theory, the term "exon" refers to any segment of an interrupted gene that is represented in the mature RNA product (B. Lewin. Genes IV Cell Press, Cambridge Mass.
1990). In theory the term "intron" refers to any segment of DNA that is transcribed but removed from within the transcript by splicing together the exons on either side of it.
Operationally, exon sequences occur in the mRNA sequence of a gene as defined by Ref. Seq ID numbers. Operationally, intron sequences are the intervening sequences within the genomic DNA of a gene, bracketed by exon sequences and having GT and AG splice consensus sequences at their 5' and 3' boundaries.

The term "microarray" refers to an ordered arrangement of hybridizable array elements, preferably polynucleotide probes, on a substrate.

The term "polynucleotide," when used in singular or plural, generally refers to any polyribonucleotide or polydeoxribonucleotide, which may be unmodified RNA or DNA or modified RNA or DNA. Thus, for instance, polynucleotides as defined herein include, without limitation, single- and double-stranded DNA, DNA including single- and double-stranded regions, single- and double-stranded RNA, and RNA including single-and double-stranded regions, hybrid molecules comprising DNA and RNA that maybe single-stranded or, more typically, double-stranded or include single- and double-stranded regions. In addition, the term "polynucleotide" as used herein refers to triple-stranded regions comprising RNA or DNA or both RNA and DNA. The strands in such regions may be from the same molecule or from different molecules. The regions may include all of one or more of the molecules, but more typically involve only a region of some of the molecules. One of the molecules of a triple-helical region often is an oligonucleotide. The term "polynucleotide"
specifically includes cDNAs. The term includes DNAs (including cDNAs) and RNAs that contain one or more modified bases. Thus, DNAs or RNAs with backbones modified for stability or for other reasons are "polynucleotides" as that term is intended herein. Moreover, DNAs or RNAs comprising unusual bases, such as inosine, or modified bases, such as tritiated bases, are included within the term "polynucleotides" as defined herein. In general, the term "polynucleotide" embraces all chemically, enzymatically and/or metabolically modified forms of unmodified polynucleotides, as well as the chemical forms of DNA and RNA
characteristic of viruses and cells, including simple and complex cells.

The term "oligonucleotide" refers to a relatively short polynucleotide, including, without limitation, single-stranded deoxyribonucleotides, single- or double-stranded ribonucleotides, RNA:DNA hybrids and double-stranded DNAs. Oligonucleotides, such as single-stranded DNA probe oligonucleotides, are often synthesized by chemical methods, for example using automated oligonucleotide synthesizers that are commercially available.
However, oligonucleotides can be made by a variety of other methods, including in vitro recombinant DNA-mediated techniques and by expression of DNAs in cells and organisms.
The terms "differentially expressed gene," "differential gene expression" and their synonyms, which are used interchangeably, refer to a gene whose expression is at a higher or lower level in one patient or test subject relative to another, for example, in a subject suffering from a disease, specifically cancer, such as breast cancer, relative to its expression in a normal or control subject. The terms also include genes whose expression is activated to a higher or lower level at different stages of the same disease. It is also understood that a differentially expressed gene may be either activated or inhibited at the nucleic acid level or protein level, or may be subject to alternative splicing to result in a different polypeptide product. Such differences may be evidenced by a change in mRNA levels, surface expression, secretion or other partitioning of a polypeptide, for example.
Differential gene expression may include a comparison of expression between two or more genes or their gene products, or a comparison of the ratios of the expression between two or more genes or their gene products, or even a comparison of two differently processed products of the same gene, which differ between normal subjects and subjects suffering from a disease, specifically cancer, or between various stages of the same disease. Differential expression includes both quantitative, as well as qualitative, differences in the temporal or cellular expression pattern in a gene or its expression products among, for example, normal and diseased cells, or among cells which have undergone different disease events or disease stages. For the purpose of this invention, "differential gene expression" is considered to be present when there is at least an about two-fold, preferably at least about four-fold, more preferably at least about six-fold, most preferably at least about ten-fold difference between the expression of a given gene in normal and diseased subjects, or in various stages of disease development in a diseased subject.
The term "over-expression" with regard to an RNA transcript is used to refer to the level of the transcript determined by normalization to the level of reference mRNAs, which might be all measured transcripts in the specimen or a particular reference set of mRNAs.

The phrase "gene amplification" refers to a process by which multiple copies of a gene or gene fragment are formed in a particular cell or cell line. The duplicated region (a stretch of amplified DNA) is often referred to as "amplicon." Often, the amount of the messenger RNA (mRNA) produced, i.e., the level of gene expression, also increases in the proportion of the number of copies made of the particular gene expressed.
The term "prognosis" is used herein to refer to the prediction of the likelihood of cancer-attributable death or progression, including recurrence, metastatic spread, and drug resistance, of a neoplastic disease, such as breast cancer. The term "prediction" is used herein to refer to the likelihood that a patient will respond either favorably or unfavorably to a drug or set of drugs, and also the extent of those responses, or that a patient will survive, following surgical removal or the primary tumor and/or chemotherapy for a certain period of time without cancer recurrence. The predictive methods of the present invention can be used clinically to make treatment decisions by choosing the most appropriate treatment modalities for any particular patient. The predictive methods of the present invention are valuable tools in predicting if a patient is likely to respond favorably to a treatment regimen, such as surgical intervention, chemotherapy with a given drug or drug combination, and/or radiation therapy, or whether long-term survival of the patient, following sugery and/or termination of chemotherapy or other treatment modalities is likely.
The term "long-term" survival is used herein to refer to survival for at least 3 years, more preferably for at least 5 years, most preferably for at least 10 years following surgery or other treatment.
The term "increased resistance" to a particular drug or treatment option, when used in accordance with the present invention, means decreased response to a standard dose of the drug or to a standard treatment protocol.
The term "decreased sensitivity" to a particular drug or treatment option, when used in accordance with the present invention, means decreased response to a standard dose of the drug or to a standard treatment protocol, where decreased response can be compensated for (at least partially) by increasing the dose of drug, or the intensity of treatment.

"Patient response" can be assessed using any endpoint indicating a benefit to the patient, including, without limitation, (1) inhibition, to some extent, of tumor growth, including slowing down and complete growth arrest; (2) reduction in the number of tumor cells; (3) reduction in tumor size; (4) inhibition (i.e., reduction, slowing down or complete stopping) of tumor cell infiltration into adjacent peripheral organs and/or tissues; (5) inhibition (i.e. reduction, slowing down or complete stopping) of metastasis;
(6) enhancement of anti-tumor immune response, which may, but does not have to, result in the regression or rejection of the tumor; (7) relief, to some extent, of one or more symptoms associated with the tumor; (8) increase in the length of survival following treatment; and/or (9) decreased mortality at a given point of time following treatment.

The term "treatment" refers to both therapeutic treatment and prophylactic or preventative measures, wherein the object is to prevent or slow down (lessen) the targeted pathologic condition or disorder. Those in need of treatment include those already with the disorder as well as those prone to have the disorder or those in whom the disorder is to be prevented. In tumor (e.g., cancer) treatment, a therapeutic agent may directly decrease the pathology of tumor cells, or render the tumor cells more susceptible to treatment by other therapeutic agents, e.g., radiation and/or chemotherapy.

The term "tumor," as used herein, refers to all neoplastic cell growth and proliferation, whether malignant or benign, and all pre-cancerous and cancerous cells and tissues.

The terns "cancer" and "cancerous" refer to or describe the physiological condition in mammals that is typically characterized by unregulated cell growth. Examples of cancer include but are not limited to, breast cancer, colon cancer, lung cancer, prostate cancer, hepatocellular cancer, gastric cancer, pancreatic cancer, cervical cancer, ovarian cancer, liver cancer, bladder cancer, cancer of the urinary tract, thyroid cancer, renal cancer, carcinoma, melanoma, and brain cancer.
The "pathology" of cancer includes all phenomena that compromise the well-being of the patient. This includes, without limitation, abnormal or uncontrollable cell growth, metastasis, interference with the normal functioning of neighboring cells, release of cytokines or other secretory products at abnormal levels, suppression or aggravation of inflammatory or immunological response, neoplasia, premalignancy, malignancy, invasion of surrounding or distant tissues or organs, such as lymph nodes, etc.
"Stringency" of hybridization reactions is readily determinable by one of ordinary skill in the art, and generally is an empirical calculation, dependent upon probe length, washing temperature, and salt concentration. In general, longer probes require higher temperatures for proper annealing, while shorter probes need lower temperatures. Hybridization generally depends on the ability of denatured DNA to reanneal when complementary strands are present in an environment below their melting temperature. The higher the degree of desired homology between the probe and hybridizable sequence, the higher the relative temperature which can be used. As a result, it follows that higher relative temperatures would tend to make the reaction conditions more stringent, while lower temperatures less so.
For additional details and explanation of stringency of hybridization reactions, see Ausubel et al., Current Protocols in Molecular Biology, Wiley Interscience Publishers, (1995).
"Stringent conditions" or "high stringency conditions", as defined herein, typically: (1) employ low ionic strength and high temperature for washing, for example 0.015 M sodium chloride/0.0015 M sodium citrate/0.1% sodium dodecyl sulfate at 50 C; (2) employ during hybridization a denaturing agent, such as formamide, for example, 50% (v/v) formamide with 0.1 % bovine serum albumin/0.1 % Ficoll/0.1 % polyvinylpyrrolidone/50mM sodium phosphate buffer at pH 6.5 with 750 mM sodium chloride, 75 mM sodium citrate at 42 C; or (3) employ 50% formamide, 5 x SSC (0.75 M NaCl, 0.075 M sodium citrate), 50 mM sodium phosphate (pH 6.8), 0.1% sodium pyrophosphate, 5 x Denhardt's solution, sonicated salmon sperm DNA
(50 g/ml), 0.1% SDS, and 10% dextran sulfate at 42 C, with washes at 42 C in 0.2 x SSC
(sodium chloride/sodium citrate) and 50% form ide at 55 C, followed by a high-stringency wash consisting of 0.1 x SSC containing EDTA at 55 C.

"Moderately stringent conditions" may be identified as described by Sambrook et al., Molecular Cloning: A Laboratory Manual, New York: Cold Spring Harbor Press, 1989, and include the use of washing solution and hybridization conditions (e.g., temperature, ionic strength and %SDS) less stringent that those described above. An example of moderately stringent conditions is overnight incubation at 37 C in a solution comprising:
20%
formamide, 5 x SSC (150 mM NaCl, 15 mM trisodiurn citrate), 50 mM sodium phosphate (pH 7.6), 5 x Denhardt's solution, 10% dextran sulfate, and 20 mg/ml denatured sheared salmon sperm DNA, followed by washing the filters in 1 x SSC at about 37-50 C.
The skilled artisan will recognize how to adjust the temperature, ionic strength, etc. as necessary to accommodate factors such as probe length and the like.

In the context of the present invention, reference to "at least one," "at least two," "at least five," etc. of the genes listed in any particular gene set means any one or any and all combinations of the genes listed.

B. Detailed Description The practice of the present invention will employ, unless otherwise indicated, conventional techniques of molecular biology (including recombinant techniques), microbiology, cell biology, and biochemistry, which are within the skill of the art. Such techniques are explained fully in the literature, such as, "Molecular Cloning:
A Laboratory Manual", 2"d edition (Sambrook et al., 1989); "Oligonucleotide Synthesis"
(M.J. Gait, ed., 1984); "Animal Cell Culture" (R.I. Freshney, ed., 1987); "Methods in Enzymology"
(Academic Press, Inc.); "Handbook of Experimental Immunology", 4th edition (D.M. Weir &
C.C. Blackwell, eds., Blackwell Science Inc., 1987); "Gene Transfer Vectors for Mammalian Cells" Q.M. Miller & M.P. Calos, eds., 1987); "Current Protocols in Molecular Biology"

(F.M. Ausubel et al., eds., 1987); and "PCR: The Polymerase Chain Reaction", (Mullis et al., eds., 1994).
1. Polymerase Chain Reaction (PCR) The purpose of the polymerase chain reaction (PCR) is to make copies of a gene in order to provide larger amounts of nucleic acid for further use. PCR is a process based on a specialized polymerase enzyme (e.g. Taq DNA polymerase), which can synthesize a complementary strand to a given DNA strand in a mixture containing the four dNTP's (sATP, dCTP, dGTP, dTTP) and two oligonucleotide primers flanking the target sequence to be amplified. The two oligonucleotide primers are used to generate an amplicon typical of a PCR reaction. A third oligonucleotide, or probe, is designed to detect the nucleotide sequence located between the two PCR primers. Although the probe design might differ, in the TagMan PCR method probe signals are controlled by the proximity of a reporter fluorescent dye and a quencher fluorescent dye. Any laser-induced emission from the reporter dye is quenched by the quenching dye when the two dyes are located close together as they are on the probe. During the amplification reaction, the polymerase enzyme (e.g. Taq DNA
polymerase) cleaves the probe in a template-dependent manner. The resultant probe fragments disassociate in solution, and signal from the released reporter dye is free from the quenching effect of the second fluorophore. One molecule of reporter dye is liberated for each new molecule synthesized, and detection of the unquenched reporter dye provides the basis for quantitative interpretation of the data.

The starting material for PCR can be DNA, cDNA, mRNA or any other polynucleotide that needs to be amplified. Since the PCR requires single-stranded DNA as template, if the starting material is double-stranded DNA, it needs to be denatured in order to produce single-stranded DNA.
As RNA cannot serve as a template for PCR, if the starting material is RNA, the first step is the reverse transcription of the RNA template into cDNA, followed by its exponential amplification in a PCR reaction. This version of PCR is generally referred to as reverse transcriptase PCR (RT-PCR). The two most commonly used reverse transcriptases are avian myeloblastosis virus reverse transcriptase (AMV-RT) and Moloney murine leukemia virus reverse transcriptase (MMLV-RT). The reverse transcription step is typically primed using specific primers, random hexamers, or oligo-dT primers, depending on the circumstances.
For example, RNA extracted from a tissue sample (e.g. FPET) can be reverse-transcribed using a GeneAmp RNA PCR kit (Perkin Elmer, CA, USA), following the manufacturer's instructions. The derived cDNA can then be used as a template in the subsequent PCR
reaction.

Although the PCR step can use a variety of thermostable DNA-dependent DNA
polynlerases, it typically employs the Taq DNA polymerise, which has a 5'-3' nuclease activity but lacks a 3'-5' proofreading endonuclease activity. Thus, TagMan PCR typically utilizes the 5'-nuclease activity of Taq or Tth polymerise to hydrolyze a hybridization probe bound to its target amplicon, but any enzyme with equivalent 5' nuclease activity can be used.
In this case, the probe is designed to be non-extendible by Taq DNA polymerase enzyme.
TagMan RT-PCR can be performed using commercially available equipment, such as, for example, ABI PRISM 7700 Sequence Detection SystemTM (Perkin-Elmer-Applied Biosystems, Foster City, CA, USA), or Lightcycler (Roche Molecular Biochemicals, Mannheim, Germany). Ina preferred embodiment, the 5' nuclease procedure is run on a real-time quantitative PCR device such as the ABI PRISM 7700TM Sequence Detection SystemTM.
The system consists of a thermocycler, laser, charge-coupled device (CCD), camera and computer. The system amplifies samples in a 96-well format on a thermocycler.
During amplification, laser-induced fluorescent signal is collected in real-time through fiber optics cables for all 96 wells, and detected at the CCD. The system includes software for running the instrument and for analyzing the data.

5'-Nuclease assay data are initially expressed as Ct, or the threshold cycle.
As discussed above, fluorescence values are recorded during every cycle and represent the amount of product amplified to that point in the amplification reaction. The point when the fluorescence signal is first recorded as statistically significant is the threshold cycle (Ct).
To minimize errors and the effect of sample-to-sample variation, RT-PCR is usually performed using an internal standard. The ideal internal standard is expressed at a constant level among different tissues, and is unaffected by the experimental treatment. RNAs frequently used to normalize patterns of gene expression are mRNAs for the housekeeping genes glyceraldehyde-3-phosphate-dehydrogenase (GAPDH) and J3-actin.

For further details of real time quantitative PCR see also Held et al., Gesn.onle Research 6:986-994 (1996). PCR is described in U.S. Patent Nos. 4,683,202, 4,683,195;
4,965,188; and 5,075,216.

2. Introns and RNA Splicing Most genes in higher euk_aryotes contain more than 100,000 nucleotide pairs, some containing more than 2 million nucleotide pairs. This is significantly longer than the nucleotide sequence required to encode an average size protein (300-400 amino acids), which is in the order of about 1000 nucleotides. Most of the extra length consists of noncoding (intron) sequences that interrupt the coding (t, -,on) sequences vvlthin the gene sequence.

Most of higher eukaryotic genes coding for mRNA, tR iA and some coding for rRNA are interrupted by intron sequences. Genes for mRNA typically have 0 to 60 introns; while genes for tRNA typically include 0 or 1 intron.
When mRNA is transcribed from DNA, at first both exon and intron sequences are transcribed into the so-called heterogeneous nuclear RNA (hnRNA) or immature RNA or pre-mRNA. However, before the RNA exits the nucleus, intron sequences are often deleted from the transcribed mRNA as a result of a process known as RNA splicing. The process of intron removal involves a precise looping process controlled by a specific nucleotide sequence abutting the exons. Almost all introns can be identified by specific consensus sequences. The first two bases of an intron are always GU, while the last two bases are always AG, but the 5' and 3' splice sites typically have consensus sequences that extend beyond the GU and AG
motifs. Splicing of mRNA takes place on a particle called spliceosome, while tRNA and rRNA are spliced by mechanisms that do not involve spliceosomes.

Introns are typically much longer than exons (sequences that are present in the mRNA). An average eukaryotic exon is about 150 nucleotides long, while a single human intron can be as long as close to 500,000 nucleotides, but typically are about nucleotides. In general, a eukaryotic gene contains much more intron than exon sequences, as illustrated by the following table (Molecular Biology of the Cell, Bruce Alberts et al., eds., 3rd edition, Garland Publishing Company, New York, N.Y., 1994, p. 340):

Table 1 Gene Gene Size MRNA Size Number of Introns (x 103 nucleotides) (x 103 nucleotides) (3-globin 1.5 0.6 2 Insulin 1.7 0.4 2 Proteinase C 11 1.4 7 Albumin 25 2.1 14 Catalase 34 1.6 12 L,DL receptor 45 5.5 17 Factor VIII 186 9 25 Thyroglobulin 300 8.7 36 In a particular embodiment of the present invention, intron sequences within a gene of interest are subjected to a selection process to identify intronic RNA
sequence or sequences that co-express with exon RNA (i.e., mRNA) sequences of the same gene. Such selected intron sequences, the expression of which correlates with the expression of exon sequences, have especially desirable properties as potential diagnostic markers: (1) because of their favorable technical performance (specifically, optimizing assay specificity and sensitivity);

and, (2) whatever biomedical importance attaches to the mRNA level of the gene is also attached to the cellular levels of intronic sequences. For example, high levels of an mRNA
species that encodes a potent growth factor are likely to correlate with high rate of growth of a cell. Intronic sequences having cellular levels that correlate with mRNA
levels of this same gene have the same likelihood to correlate with high growth rate of a cell.
Such selected intronic sequences can then be used to screen valuable tissue specimens to search for clinical correlations and diagnostic, predictive or prognostic significance.

An exemplary process for selecting intron sequences that co-express with the mRNA
of the same gene is as follows. Briefly, for any gene of interest, a set of relevant tissues from a population of patients of interest are assayed to measure the levels of a set of intronic and mRNA sequences. The intronic sequences found to have the highest Pearson correlation coefficient for co-expression with exon RNA (mRNA) sequences are then selected. The number of patients studied in this process is preferably at least above 50 and more preferably at least about 100.

In a specific example, the biomedical issue of interest regards patients with breast cancer and the gene of interest can be the tumor growth marker Ki-67. In this case, tumors from 50 or more breast cancer patients are used for measurement of Ki-67 mRNA
levels and the levels of sequences from multiple Ki-67 introns, and the introns having the highest Pearson correlation coefficient for co-expressing with exon RNA are selected.
An advantage of this process is that the selection of the preferred intronic sequence can be carried out with tissue specimens that are relatively easily obtained and abundant (for example, specimens that lack valuable attached clinical records). Because such tissue can provide large amounts of RNA to screen, it will be possible to detect gene expression signals from even suboptimal probes. The highly sensitive and specific assays based on the selected intronic sequences then can be used to screen valuable tissue specimens, for example, specimens attached to important clinical information, such as disease recurrence, death, or response to defined therapeutic drugs or treatment regimens.

3. Gene Expression Profiling Using Intron-based PCR Primer/Probe Sets At present, PCR primers and probes are designed based upon the mRNA or cDNA
sequence, without considering the intron sequences. Indeed, introns are usually regarded as "packaging" material that is removed during splicing and. generally rapidly degraded.
The present invention is based on the unanticipated experimental finding that intron RNAs can be readily detected by RT-PCR, even using highly degraded RNA from fixed, paraffin-embedded tissue specimens. In particular, it has been found that in gene expression profiling for a given gene RT-PCR signals from intron-based probe/primer sets can be as large, or larger, than the signals from exon-based RT-PCR signals. While this finding is supported by a few recent findings with certain mRNA species, it is not in accord with the prevailing view that introns are very rapidly degraded following splicing (Thomas et al., T.

Virol. 76:532-40 [2002]; Clement et al., J. Biol. Chem. 276:16919-30 [2001];
Sharp et al., Ann. Rev. Biochem. 55:1119-1150 [1986])..
Also unexpected, the experimental findings underlying the present invention indicate that intronic RNA can be used for gene expression profiling, because the tissue amounts of expressed intron and exon sequences tend to be correlated. This result is unanticipated because scant or no evidence exists that the ratio of the overall rate constants for synthesis and turnover of transcribed intron and exon sequences are similar. In fact, the scientific literature provides evidence for the complexity of pre-mRNA and spliced intron turnover.
For example, pre-mRNA can exist in multiple kinetic pools (Elliott and Rosbash, Exp. Cell Res.
229:181-8 [1996]), with subpopulations containing intron RNAs that are not efficiently spliced out and are transported to the cytoplasm in "immature" mRNA species, where they can decay at rates different than nuclear intron RNA sequences (Wang et al., Proc. Natl.
Acad. Sci. USA 94:4360-5 [1997]). Evidence exists that certain spliced intron RNAs enter the cytoplasm in lariat structure (Clement et al., RNA 5:206-20 [1999]).
Finally, data presented here indicate that intron sequences can serve as diagnostic or prognostic molecular markers. Examining four mRNAs previously demonstrated to be prognostic in cancer, it is shown that their corresponding intron sequences are also prognostic, and in the same directions as the parent transcribed exon sequences (i.e., either positively or negatively prognostic).
In brief, the approach of the invention has been demonstrated as follows. Co-pending U.S. Patent No. 7,081,340 describes a set of genes that predict likelihood of breast cancer recurrence. In that study, the levels of transcribed exon sequences in fixed paraffin-embedded breast cancer tissue specimens from 146 patients were measured by RT-PCR using exon-based PCR primer/probe sets. In the study described here, RT-PCR assays were created to measure the levels of transcribed intron sequences within four of the previously identified marker genes, and then used to screen RNA from 60 fixed paraffin-embedded biopsy specimens (representing 60 different patients, a subset of the patients evaluated in the previous study). The data presented in the examples below show that for each gene the introns and exons are co-expressed, and that the introns predict risk of disease recurrence as predicted by the previous exon-based data.

3. Design of Intron-Based PCR Primers and Probes According to one aspect of the present invention, PCR primers and probes are designed based upon intron sequences present in the gene to be amplified.
Accordingly, the first step in the primer/probe design is the delineation of intron sequences within the genes.
This can be done by publicly available software, such as the DNA SLAT software developed by Kent, W.J., Genome Res. 12(4):656-64 (2002), or by the BLAST software including its variations. Subsequent steps follow well established methods of PCR primer and probe design.
In order to avoid non-specific signals, it is important to mask repetitive sequences within the introns when designing the primers and probes. This can be easily accomplished by using the Repeat Masker program available on-line through the Baylor College of Medicine, which screens DNA sequences against a library of repetitive elements and returns a query sequence in which the repetitive elements are masked. The masked intron sequences can then be used to design primer and probe sequences using any commercially or otherwise publicly available primer/probe design packages, such as Primer Express (Applied Biosystems); MGB assay-by-design (Applied Biosystems); Primer3 (Steve Rozen and Helen J. Skaletsky (2000) Primer3 on the WWW for general users and for biologist programmers.
In: Krawetz S, Misener S (eds) Bioinfornraiics Methods and Protocols: Methods in Molecular Biology. Humana Press, Totowa, NJ, pp 365-386).
The most important factors considered in PCR primer design include primer length, melting temperature (Tm), and G/C content, specificity, complementary primer sequences, and 3'-end sequence. In general, optimal PCR primers are generally 17-30 bases in length, and contain about 20-80%, such as, for example, about 50-60% G+C bases. Tm's between 50 and 80 C, e.g. about 50 to 70 C are typically preferred.
For further guidelines for PCR primer and probe design see, e.g. Dieffenbach, C.W. et al., "General Concepts for PCR Primer Design" in: PCR Primer, A Laboratory Manual, Cold Spring Harbor Laboratory Press, New York, 1995, pp. 133-155; Innis and Gelfand, "Optimization of PCRs" in: PCR Protocols, A Guide to Methods and Applications, CRC
Press, London, 1994, pp. 5-11; and Plasterer, T.N. Primerselect: Primer and probe design.
Methods Mol. Biol. 70:520-527 (1997).

4. Applications The methods of the present invention, and specifically, the intron-based PCR
primers and probes herein, utility in all fields where amplification of a nucleic acid (including RNA, DNA and, in general, all oligo- and poly nucleotides) representing a gene or a gene fragment is required. Thus the PCR primers and probes designed in accordance with the present invention can be used to amplify individual genes, or multiple genes present in a biological sample for the purpose of gene expression profiling by any methodology including, without limitation, gene expression profiling relying on quantitative PCR (e.g.
quantitative RT-PCR), and microarray analysis, and bead-based assays.

For example, in a specific embodiment of the microarray technique, PCR
amplified inserts of cDNA clones are applied to a substrate in a dense array. Preferably at least 10,000 nucleotide sequences are applied to the substrate. The microarrayed genes, immobilized on the microchip at at least 10,000 elements each, are suitable for hybridization under stringent conditions. Fluorescently labeled cDNA probes may be generated through incorporation of fluorescent nucleotides by reverse transcription of RNA extracted from tissues of interest.
Labeled cDNA probes applied to the chip hybridize with specificity to each spot of DNA on the array. After stringent washing to remove non-specifically bound probes, the chip is scanned by confocal laser microscopy or by another detection method, such as a CCD camera.
Quantitation of hybridization of each arrayed element allows for assessment of corresponding mRNA abundance. With dual color fluorescence, separately labeled cDNA probes generated from two sources of RNA are hybridized pairwise to the array. The relative abundance of the transcripts from the two sources corresponding to each specified gene is thus determined simultaneously. The miniaturized scale of the hybridization affords a convenient and rapid evaluation of the expression pattern for large numbers of genes. Such methods have been shown to have the sensitivity required to detect rare transcripts, which are expressed at a few copies per cell, and to reproducibly detect at least approximately two-fold differences in the expression levels (Schena et al., Proc. Natl. Acad. Sci. USA 93(2):106-149 (1996)).
Microarray analysis can be performed by commercially available equipment, following manufacturer's protocols, such as by using the Affymetrix GenChip technology, or Agilent's microarray technology.
An important aspect of the present invention is to use intron-based gene amplification as part of gene expression profiling to match patients to best drugs or drug combinations, and to provide prognostic information. For example, the measured expression of genes in cancer tissue (e.g. biopsied breast cancer tissue) can be used to predict the likelihood of long-term, disease-free survival of patients following surgery and/or other cancer therapy, or to predict patient response to a particular therapeutic approach. For this purpose it is typically necessary to correct for (normalize away) both differences in the amount of RNA assayed and variability in the quality of the RNA used. Therefore, the assays of the invention usually measure and incorporate the expression of certain normalizing genes, including well known reference genes, such as GAPDH and Cypl. Alternatively, normalization can be based on the mean or median signal (Ct) of all of the assayed genes or a large subset thereof (global normalization approach). On a gene-by-gene basis, the measured normalized amount of a patient tumor mRNA is compared to the amount found in a cancer, e.g. breast cancer tissue reference set.
The number (N) of cancer, e.g. breast cancer, tissues in this reference set should be sufficiently high to ensure that different reference sets (as a whole) behave essentially the same way. If this condition is met, the identity of the individual breast cancer tissues present in a particular set will have no significant impact on the relative amounts of the genes assayed. Usually, the breast cancer tissue reference set consists of at least about 30, preferably at least about 40 different fixed, paraffin-embedded (FPE) breast cancer tissue specimens. Unless noted otherwise, normalized expression levels for each mRNA/tested tumor/patient will be expressed as a percentage of the expression level measured in the reference set. IMfore specifically, the reference set of a sufficiently high number (e.g., 40) tumors yields a distribution of normalized levels of each mRNA species. The level measured in a particular tumor sample to be analyzed falls at some percentile within this range, which can be determined by methods well known in the art.
In a Phase II study of gene expression in paraffin-embedded, fixed tissue samples of invasive breast carcinoma, the overexpression of any of the following genes in the breast cancer tissue was found to indicate a reduced likelihood of survival without cancer recurrence following surgery: FOXM1; PRAMS; SKT15, Ki-67; CA9; NME1; SURV; TFRC; YB-1;
RPS6KB1; Src; Chkl; CCNB1; Chk2; CDC25B; CYP3A4; EpCAM; VEGFC; hENT1;
BRCA2; EGFR; TK1; VDR.
In the same study, the overexpression of any of the following genes in breast cancer indicates a better prognosis for survival without cancer recurrence following surgery: B1c12;
CEGP1; GSTM1; PR; BBC3; GATA3; DPYD; GSTM3; Dl; EstRl; p27; XIAP; IGF1R;
AK055699; P13KC2A; TGFB3; BAGI1; pS2; WISP1; HNF3A; NFKBp65.

In this same Phase II study of gene expression in paraffin-embedded, fixed tissue samples of ER-positive breast cancer, overexpression of the following genes was indicative of a reduced likelihood of survival without cancer recurrence following surgery:
PRAME;
FOXMI; EPHXI; HIF1A; VEGFC; Ki-67; VDR; NME1. Some of these genes (PRAME;
FOXMI; VEGFC; Ki-67; VDR; and NME1) were also identified as indicators of poor prognosis in the previous analysis, not limited to ER-positive breast cancer.
The overexpression of the remaining genes (EPHXI and HIFIA) was found to be negative indicator of disease free survival in ER-positive breast cancer only.
Overexpression of the following genes in ER-positive cancer was found to be indicative of a better prognosis for survival without cancer recurrence following surgery: Bcl-2; DIABLO; IGF1R;
GSTM3. Of the latter genes, Bcl-2; IGFR1; and GSTM3 have also been identified as indicators of good prognosis in the previous analysis, not limited to ER-positive breast cancer.
The overexpression of DIABLO appeared to be positive indicator of disease free survival in ER-positive breast cancer only. For further details see, co-pending U.S. Patent App. Pub.
No. 2005/0196782, The studies described above were performed essentially as described in Example below, except gene amplification was studied using exon-based amplicons. For further details, see copending U.S. Patent No. 7,081,340. As attested by the data set forth in Example 2. the data obtained using intron-based amplicons show excellent correlation with the earlier data, and typically provide the added benefit of increased sensitivity.

The findings of the previous Phase II study of invasive breast ductal carcinoma were subjected to multivariate stepwise analysis, using the Cox Proportional Hazards Model using the following equation:
RR=exp[coef(geneA) x Ct(geneA) + coef(geneB) x Ct(geneB) + coef(geneC) x Ct(geneC) + ............... In this equation, coefficients for genes that are predictors of beneficial outcome are positive numbers and coefficients for genes that are predictors of unfavorable outcome are negative numbers. The "Ct" values in the equation are ACts, i.e. reflect the difference between the average normalized Ct value for a population and the normalized Ct measured for the patient in question. The convention used in the analysis has been that ACts below and above the population average have positive signs and negative signs, respectively (reflecting greater or lesser mRNA abundance). The relative risk (RR) calculated by solving this equation indicated if the patient has an enhanced or reduced chance of long-term survival without cancer recurrence.
In a multivariate analysis, using an interrogation set including a reduced number of genes, the following ten-gene sets have been identified as having particularly strong predictive value of patient survival without cancer recurrence following surgical removal of primary tumor.
1. Bc12, cyclinGl, NFKBp65, NME1, EPHX1, TOP2B, DR5, TERC, Src, DIABLO;

2. Ki67, XIAP, hENT1, TS, CD9, p27, cyclinGl, pS2, NFKBp65, CYP3A4;
3. GSTM1, XIAP, Ki67, TS, cyclinGl, p27, CYP3A4, pS2, NFKBp65, ErbB3;

4. PR, NME1, XIAP, upa, cyclinGl, Contig51037, TERC, EPHX1, ALDHIA3, CTSL;

5. CA9, NME1, TERC, cyclinGl, EPHX1, DPYD, Src, TOP2B, NFKBp65, VEGFC;

6. TFRC, XIAP, Ki67, TS, cyclinGl, p27, CYP3A4, pS2, ErbB3, NFKBp65.

In a multivariate analysis, using an interrogation set including all genes identified, the following ten-gene sets have been identified as having particularly strong predictive value of patient survival without cancer recurrence following surgical removal of primary tumor.
1. Bcl2, PRAME, cyclinGl, FOXM1, NFKBp65, TS, XIAP, Ki67, CYP3A4, p27;
2. FOXM1, cyclinGl, XIAP, Contig51037, PRAME, TS, Ki67, PDGFRa, p27, NFKBp65;
3. PRAME, FOXM1, cyclinGl, XIAP, Contig51037, TS, Ki6, PDGFRa, p27, NFKBp65;
4. Ki67, XIAP, PRAME, hENT1, contig51037, TS, CD9, p27, ErbB3, cyclinGl;
5. STK15, XIAP, PRAME, PLAUR, p27, CTSL, CD18, PREP, p53, RPS6KB1;

6. GSTM1, XIAP, PRAME, p27, Contig51037, ErbB3, GSTp, EREG, ID1, PLAUR;
7. PR, PRAME, NME1, XIAP, PLAUR, cyclinGl, Contig51037, TERC, EPHX1, DR5;

8. CA9, FOXM1, cyclinGl, XIAP, TS, Ki67, NFKBp65, CYP3A4, GSTM3, p27;
9. TFRC, XIAP, PRAME, p27, Contig51037, ErbB3, DPYD, TERC, NME1, VEGFC;
10. CEGP1, PRAMS, hENT1, XIAP, Contig51037, ErbB3, DPYD, NFKBp65, ID 1, TS.
Using the same multivariate analysis approach for ER-positive breast cancer, the following ten-gene sets have been identified as having particularly strong predictive value of patient survival without cancer recurrence following surgical removal of primary tumor.

1. PRAME, p27, IGFBP2, HIF1A, TIMP2, ILT2, CYP3A4, ID1, EstR1, DIABLO;
2. Contig51037, EPHX1, Ki67, TIMP2, cyclinGl, DPYD, CYP3A4, TP, AIB1, CYP2C8;
3. Bc12, hENT1, FOXM1, Contig51037, cyclinGl, Contig46653, PTEN, CYP3A4, TIIMP2. AREG-, 4. HIF1A, PRAME, p27, IGFBP2, TIMP2, ILT2, CYP3A4, ID1, EstRl, DIABLO;
5. IGF1R, PRAME, EPHX1, Contig51037, cyclinGl, Bc12, NME1, PTEN, TBP, TIMP2;
6. FOXM1, Contig51037, VEGFC, TBP, HIF1A, DPYD, RAD51C, DCR3, cyclinGl, BAGI;
7. EPHX1, Contig51037, Ki67, TIMP2, cyclinGl, DPYD, CYP3A4, TP, AIB1, CYP2C8;
8. Ki67, VEGFC, VDR, GSTM3, p27, upa, ITGA7, rhoC, TERC, Pinl;

9. CDC25B, Contig51037, hENT1, Bc12, HLAG, TERC, NME1, upa, ID1, CYP;
10. VEGFC, Ki67, VDR, GSTM3, p27, upa, ITGA7, rhoC, TERC, Pinl;
11. CTSB, PRAME, p27, IGFBP2, EPHX1, CTSL, BAD, DR5, DCR3, XIAP;
12. DIABLO, Ki67, hENT1, TIMP2, ID1, p27, KRT19, IGFBP2, TS, PDGFB;
13. p27, PRAME, IGFBP2, HIF1A, TIMP2, ILT2, CYP3A4, 1131, EstRl, DIABLO;
14. CDH1; PRAME, VEGFC; HIF1A; DPYD, TUVIP2, CYP3A4, EstRl, RBP4, p27;
15. IGFBP3, PRAME, p27, Bc12, XIAP, EstRl, Ki67, TS, Src, VEGF;
16. GSTM3, PRAMS, p27, IGFBP3, XIAP, FGF2, hENT1, PTEN, EstRl, APC;
17. hENT1, Bc12, FOXM1, Contig51037, CyclinGl, Contig46653, PTEN, CYP3A4, TIMP2, AREG;
18. STK15, VEGFC, PRAME, p27, GCLC, hENT1, ID1, TIMP2, EstRl, MCP1;
19. NME1, PRAM, p27, IGFBP3, XIAP, PTEN, hENT1, Bc12, CYP3A4, HLAG;
20. VDR, Bc12, p27, hENT1, p53, PI3KC2A, EIF4E, TFRC, MCM3, IDl;
21. EIF4E, Contig51037, EPHXl, cyclinGl, Bc12, DR5, TBP, PTEN, NME1, HER2;
22. CCNB1, PRAME, VEGFC, HIF1A, hENT1, GCLC, TIMP2, ID1, p27, upa;
23. 1131, PRAME, DIABLO, hENT1, p27, PDGFRa, NME1, BIN1, BRCA1, TP;
24. FBXO5, PRAME, IGFBP3, p27, GSTM3, hENT1, XIAP, FGF2, TS, PTEN;
25. GUS, HIA1A, VEGFC, GSTM3, DPYD, hENT1, FBXO5, CA9, CYP, KRT18;
26. Bclx, Bc12, hENT1, Contig51037, HLAG, CD9, ID1, BRCA1, BI1"T1, HBEGF, In view of the excellent correlation between exon-based and intron-based gene expression profiling results (see Example 2), the same gene sets are expected to have similar prognostic value when gene expression profiling is based on the quantitation of RT-PCR
signals from intron-based primer/probe sets.
Further details of the invention will be apparent from the following non-limiting examples.

Example 1 Design and Use of Intron-Specific PCR Primer/Probe Sets RNA was extracted from formalin-fixed, paraffin-embedded (FPET) breast cancer biopsy specimens (Clinomics Biosciences Inc., Pittsfield, MA) as follows.
Three 10 M
sections were cut and placed in a 1.5 ml tube. Paraffin was removed by xylene extraction (lml, 3 times) followed by ethanol wash (lml, twice). RNA was isolated from sectioned tissue blocks using the MasterPureTM Purification kit (Epicentre, Madison, WI). RNA was quantitated by the RiboGreen Fluorescence method (Molecular Probes). Twenty FPET RNA
samples were then pooled and used as described below.

First-strand cDNA was synthesized using Qiagen's Omniscript Reverse Transcriptase with pooled gene specific primers (reverse primers shown in Figure 2) random hexamers and RNase Inhibitor, using pooled FPET RNA (400 ng). A no reverse transcriptase (RT) reaction was also performed with 150 ng of pooled FPET RNA, sufficient RNA to perform the Taqman amplification at 5 ng/well.
Table 2 Reagents RT No RT Final cone Vol Vol ( l) Ll) 1OX Buffer RT 4 2 1X
dNTP mix, 5mM each 2 500 M
dNTP 4 each ABI Random hexamer, 0.5 50 M 1 1.25pM
GSP pool, 1 M 2 1 50nM
ABI RNase Inhibitor, 1 20U/ 1 1 20U/rxn 0 8U or Omniscript RT, 4U/pl 2 OU/rxn Nuclease free water 10 5.5 Pooled FPET RNA (164 8 n 1 16 65.6 n 1 Total vol 40 20 37 C, 60 min, Reaction conditions: 93 C, 5 min TagMan Assay TaqMan assays for the 48-gene panel were carried out in triplicate wells with reaction volume of 25 l and RNA input of 5 ng per assay. A "no RT " reaction for each gene was carried out in a single well as a control to verify that RNA rather than DNA
signals were being measured. Real time quantitation was performed on the ABI 7700 using the following parameters:
Cycling conditions: 95 C, 10 min for one cycle, 95 C, 20 sec followed by 60 C, sec, 40 cycles.

Volume reaction: 25 l.
Dye layer setting: FAM, (the passive reference is ROX) Results Intron specific Taqman primer-probe sets were designed based on masked introns of CEGP1, FOXM1, PRAME and STK15.genes, To delineate intron sequences within the genes, the NCBI reference sequence for each mRNA (NM_XXXXXX) was aligned to the human genome using the BLAST-like alignment tool (BLAT) program available at the University of Santa Cruz on-line genome resource site (http://genome.ucsc.edu). Intron sequences were then searched for repetitive sequences using the Repeat Masker program available on-line through the Baylor College of Medicine (http://searchlauncher.bcm.tmc.edu/seq-util/seq-util.html). Repeat sequences, such as Alu repeats, are identified by this program and masked. It is important to exclude these sequences prior to designing primer-probes because they yield strong, non-specific signals. The masked intron sequences (Figures 1A-M) were then used to design Taqman primer-probe sets using Primer Express (ABI). Other programs suitable for primer-probe sets include, for example, the newer primer probe design program for I GB assays-by-design (ABI). The amplicons for each primer-probe set are delineated in bold font in Figure 1. Each specific primer-probe set is shown in Figure 2.
The intron-specific primer-probe sets (test genes) were used together with their corresponding exon-specific primer-probe set (references gene) in standard Taqman gene expression profile experiments using pooled FPET RNA. Normalized expression was calculated by the formula 2 Ct where ACt is the difference between the Cts of the test gene primer-probe set and the reference gene primer-probe sets [Ct (reference)-Ct (test)].

Example 2 A Phase II Study of Gene Expression in Premalignant and Malignant Breast Tumors A gene expression study was designed and conducted with the primary goal to molecularly characterize gene expression in paraffin-embedded, fixed tissue samples of invasive breast ductal carcinoma, and to explore the correlation between such molecular profiles and disease-free survival.
Study design Molecular assays were performed on paraffin-embedded, formalin-fixed primary breast tumor tissues obtained from 60 individual patients diagnosed with breast cancer. All patients underwent surgery with diagnosis of invasive carcinoma of the breast.
Patients were included in the study only if histopathologic assessment, performed as described in the Materials and Methods section, indicated adequate amounts of tumor tissue and homogeneous pathology.
Materials and Methods Each representative tumor block was characterized by standard histopathology for diagnosis, semi-quantitative assessment of amount of tumor, and tumor grade. A
total of 6 sections (10 microns in thickness each) were prepared and placed in two Costar Brand Microcentrifuge Tubes (Polypropylene, 1.7 mL tubes, clear; 3 sections in each tube). If the tumor constituted less than 30% of the total specimen area, the sample may have been crudely dissected by the pathologist, using gross microdissection, putting the tumor tissue directly into the Costar tube.
If more than one tumor block was obtained as part of the surgical procedure, all tumor blocks were subjected to the same characterization, as described above, and the block most representative of the pathology was used for analysis.
Gene Expression Analysis mRNA was extracted and purified from fixed, paraffm-embedded tissue samples, and prepared for gene expression analysis as described above.

Molecular assays of quantitative gene expression were performed by RT-PCR, using the ABI PRISM 7900 Sequence Detection SystemTM (Perkin-Elmer-Applied Biosystems, Foster City, CA, USA). ABI PRISM 7900TH consists of a thermocycler, laser, charge-coupled device (CCD), camera and computer. The system amplifies samples in a 384-well format on a thermocycler. During amplification, laser-induced fluorescent signal is collected in real-time through fiber optics cables for all 384 wells, and detected at the CCD.
The system includes software for running the instrument and for analyzing the data.

Analysis and Results Tumor tissue was analyzed for expression of 48 different RNA sequences representing products of 37 different genes. The threshold cycle (Ct) values for each patient were normalized based on the median of all genes for that particular patient.
Clinical outcome data were available for all patients from a review of registry data and selected patient charts.

Outcomes were classified as:
0 died due to breast cancer or to unknown cause or alive with breast cancer recurrence;
1 alive without breast cancer recurrence or died due to a cause other than breast cancer Analysis was performed by:

Analysis of the relationship between normalized gene expression and the time to outcome (0 or 1 as defined above) where patients who were alive without breast cancer recurrence or who died due to a cause other than breast cancer were censored.
This approach was used to evaluate the prognostic impact of individual genes and also sets of multiple genes.
For each gene a Cox Proportional Hazards model (see, e.g. Cox, D. R., and Oakes, D.
(1984), Analysis of Survival Data, Chapman and Hall, London, New York) was defined with time to recurrence or death as the dependent variable, and the expression level of the gene as the independent variable. The genes that have a p-value < 0.05 in the Cox model were identified. For each gene, the Cox model provides the relative risk (RR) of recurrence or death for a unit change in the expression of the gene. One can choose to partition the patients into subgroups at any threshold value of the measured expression (on the Ct scale), where all patients with expression values above the threshold have higher risks and all patients with expression values below the threshold have lower risk, or vice versa, depending on whether the gene is an indicator of poor (RR>1.01) or good (RR<1.01) prognosis. Thus, any threshold value will define subgroups of patients with respectively increased or decreased risk.
Table 3, below, shows pairwise correlation of expression (presented by correlation coefficients) between the tested introns and exons for the genes CEGP1, FOXM1, PRAME, and STK15. For two of the four genes, CEGP1 and PRAME, introns were found that yielded correlation coefficients [for co-expression with their respective exons] above 0.90. In the case of STK15, one intron correlated with exon expression with a correlation coefficient -0.80. For FOXM1, intron:exon expression correlations were significantly lower. In this last case, however, it seems likely that actual expression may be highly correlated but not detectable for a technical reason. Expression of the FOXM1 exon in many patients was beneath the detection threshold of the assay, which potentially prevents detection of high correlations that may exist. If this hypothesis is correct, FOXM1 introns would still register as negative clinical prognostic markers as previously demonstrated for FOXM1.
As shown later, this result occurs.
Figures 3, 4 and 5 show that the pairwise correlation of expression of the tested RNAs against CEGP1, PRAME and STK15 exon RNAs. As shown, respective introns of these genes yielded the highest correlations. It is noteworthy that the panel of 48 genes included genes that we selected, by several bioinformatics-based strategies, as particularly likely to correlate in expression with CEGP1, PRAME, STK15, and FOXM1. Those non-intron-based strategies were most successful in the case of STK15, as several candidate genes had expression correlation coefficients in the range of 0.6-0.7.

Table 3. Correlations between Intron and Exon Expression for Four Genes ExpressionCorrelation Coefficient {R}
CEGP1intronl.I CEGPIintron3.1 CEGP1intron4.1 CEGPlintron5.1 CEGPI.2 CEGP1 intronl .1 1.00 CEGP1 intron3.1 0.89 1.00 CEGP1 intron4.1 0.97 0.82 1.00 CEGPlintron5.1 0.91 0.87 0.88 1.00 CEGPI.2 0.91 0.80 0.90 0.87 1.00 FOXM1 intron3.3 FOXMI intron5.1 FOXM1 intron7.1 FOXMI.1 FOXMI intron3.3 1.00 FOXM1 intron5.1 0.48 1.00 FOXM1 intron7.1 0.54 0.73 1.00 FOXM1.1 0.44 0.33 0.38 1.00 STK15intronl.1 STK15intron2.1 STK15intron4.1 STK15.2 STK15intronl.1 1.00 STK15intron2.1 0.78 1.00 STK15intron4.1 0.69 0.74 1.00 STK15.2 0.63 0.70 0.78 1.00 PRAMEintron2.1 PRAME.3 PRAMEintron2.1 1.00 PRAME.3 0.97 1.00 Table 4, below, shows the impact upon patient survival of expression of CEGP1, FOXM1, PRAME, and STK15, exons and introns. The parent exons all had statistically significant impact on relative risk [RR], as we previously determined, except in the case of FOXM1. Because the present study evaluated 60 patients from the original 146 patient group, the FOXM1 marker may have fallen from significance because the statistical hazard of examining a reduced data set. Very notably, for all four tested genes, intron expression significantly impacted RR, and in the same direction as the parent exons.

Table 4. Cox Model Results for 60 Patients with Breast Cancer Prognostic Correlations Gene Coef - RR=exp(coef) se(coef) z p CEGP1.2 -0.202 0.817 0.050 -4.024 0.00006 CEGPlintronl.1 -0.329 0.720 0.087 -3.771 0.00016 CEGPI intron3.1 -0.261 0.770 0.078 -3.335 0.00085 CEGPlintron4.1 -0.275 0.760 0.073 -3.774 0.00016 CEGP1 intron5.1 -0.312 0.732 0.082 -3.817 0.00014 FOXMI.1 0.175 1.192 0.136 1.289 0.19700 FOXM1 intron3.3 0.304 1.355 0.120 2.523 0.01160 FOXMlintron5.1 0.514 1.673 0.195 2.639 0.00832 FOXM1 intron7.1 0.546 1.726 0.182 2.993 0.00276 PRAME.3 0.125 1.133 0.054 2.294 0.02180 PRAMEintron2.1 0.125 1.133 0.052 2.397 0.01650 STK15.2 0.692 1.998 0.201 3.450 0.00056 STK15intronl.1 0.357 1.429 0.149 2.400 0.01640 STKl5intron2.1 0.391 1.479 0.154 2.536 0.01120 STK15intron4.1 0.410 1.506 0.133 3.084 0.00204 A common perception exists that steady state levels of transcribed exon sequences greatly exceed those of transcribed intron sequences (Sharp et al. Alan. Rev.
Biochein. 55:
1119-50 [1986]). Nevertheless, our examination of CEGP1, FoxMl, PRAIVIE and exon and intron expression, using TaqMan[TM] RT-PCR to assay RNA from fixed paraffin-embedded breast cancer tissue, demonstrated that intron and exon signal intensities were in the same range, and in all cases in the useful detection range of the assay [data not shown].
The detection of intronic RNA in this study is all the more notable because the tissue used was fixed in formalin, which degrades RNA, and thus substantially limits the ability to detect RNA (T.E. Godfrey et al. J. Mol. Diag. 2: 84-91 [2000]). In the case of CEGP1 three of the tested introns yielded lower signals and one a higher signal than the exon. In the case of FOXM1, five of nine tested introns yielded higher signals than the exon. In the case of PRAME signal intensities from the tested intron and exon were nearly identical. Finally, for STK15 all introns had signal intensities that were 1/4 to 1/20 those of the exon, but were still in the useful range of the assay. Thus, these results indicate that steady state levels of expressed introns are adequate for use of intron RNAs as molecular markers.

The scope of the claims should not be limited by the preferred embodiments set forth in the examples, but should be given the broadest interpretation consistent with the description as a whole.

SEQUENCE LISTING
<110> GENOMIC HEALTH, INC.

<120> USE OF INTRONIC RNA TO MEASURE GENE EXPRESSION
<130> 80439-73 <140> WO PCT/US2004/005287 <141> 2004-02-19 <150> US 60/448,991 <151> 2003-02-20 <160> 67 <170> FastSEQ for Windows Version 4.0 <210> 1 <211> 1566 <212> DNA
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<221> misc_feature <222> (1126) ... (1518) <223> n= a, t, c, or g <220>
<221> intron <222> (0) ... (0) <223> MGB-CEGP1 int 1.1 <400> 1 gtgagtgtcc ggccgcgggg gcgcacctgg cacagcaggc agggccagga agagtgttta 60 ggtccccggc ggagtccaga gccgggcgcg cggggctcgg ggctggcggc tgcagctccg 120 cgggggcctc tgctcccccc gggacctcac ccgccggccg ggccaaggcg ccacgaccgc 180 tggggccctg agtccttcgg cccggcctcg gacccggagc tgctgacggt tcccgccccg 240 gtccggatgc ctccagagcg cctgctagtc agaccgtcgc cggcgagcag gcaggagggt 300 gcggaccctg gccttggggt cccgcgcctc agcgtaggcg gggaaactga gggccgggcc 360 gggcacatcc gcgaggcggt ggcagctttg ccgtttcttt ctttgggggc cggcaagttc 420 tgctgatggc ttcggggtgg gctccagaga cttttctgtc agcggaacag cgcctgttcc 480 gatctgggaa ttaccctgaa gcagcaacaa gcctaggttt tcagcagaga actttggttt 540 ccagagagga ctctggacgt gctgtgctta ctggacttgc aatactttca aaatgctttt 600 gtttttaatt aatatcctgg agtagtgtca acccaggaaa tacttctgcc aaggcgggtt 660 tccaggttga gaggatgggc aggggtggga gtgcaggggg ccggccatgg ggacaccatc 720 cccgcttcgc agcatctgag agccctggat gacatctgct ccgatcccgg ggcagacttc 780 ccataaatac tctaaaccag cnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 840 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 900 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 960 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1020 nnnnnnnctc tgagctccga gaaagctgac agacagctgc ttggtgttca gagcttgtct 1080 gtccgtttgg tcctttcctc ctttagcggg catgtaggta ctattnnnnn nnnnnnnnnn 1140 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1200 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1260 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1320 34a nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1380 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1440 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1500 nnnnnnnnnn nnnnnnnnca catggcctgg gagcctgtac caggtgtcag ctgtgctctt 1560 ttgcag 1566 <210> 2 <211> 4985 <212> DNA
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<221> misc_feature <222> (4295) ... (4352) <223> n= a, t, c, or g <220>
<221> intron <222> (0) ... (0) <223> MGB-CEGP1 int 3.1 <400> 2 gtacctctgc ccagctgtgg atgggggcag agccacatct gagaccctct cccttgcacg 60 cgcacacaca cactgactct agnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 120 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 180 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 240 nnnnnnnnnn nnnatcttta catagaatac atttcaaaca tgactagatg tctcaggagc 300 aatatagtgg atgatctgcc aagtttttca aaaaggtgct gaaaaccaca gcaccagtat 360 gagcctgctc cctgctctgg gtgggtaggg aggaggctgg atccttccca tgcagacttt 420 caatgaagtg ccctgttttc agccccaagc tagatccggc ccttccatgt tttgcatttt 480 tgagctccga ggggcagaag ggctccctcc ctggactttc cgtgctgtgg tttccttcgc 540 ctacgtcacc atttatcatt cctctgtaaa tttgccggaa actcttctct tctgatgtcc 600 ttctcttcat tctctttgct ttgagtttat accttttttc attcctctgt tacttagtag 660 attcttgaga ggaaggggca ttaagtacat gtggccaatc agttattttt aactgaatgt 720 catcctttta actcttccct gctctttctt aagctaaaga gtcacatttt ggtggctgtg 780 ttcctcttgg agttgcatct gcctattttt aggggaagtg ccctaaatac tagcctatta 840 acccctttgg ccatgtgctg cttattcttt cccattactt aagaatgagg tcattttaat 900 ttcttctact atttaatcac aaatttatag attgttttaa tcctggtctt ggtaactttt 960 caagggtttc ttcatggaag atgatttttg tctcattttc caaggatggc agctcacacc 1020 ttatacttaa ctagaatacc tgtttgggta ccaagaaaaa ttgtcagagg aacccccagg 1080 ggccaatggg tttgatggct atcatcaccc agagcctgct cattctcagc gtttggggcg 1140 34b gggaagtcac acatactggc tttgatcagg cagatttcct atcttgtgcc aggtgtggcc 1200 cttgataaag tagcagttgg gtttcatttt cctgccaggt tctctggggt cattggtgtg 1260 ccctgcactc ttgtccaatg taggccaaat tcgagatggg aatgaattag gaggccagtg 1320 gcacagagtg atccgaatct cagggcatct ctccttttga ttgctcaaag ctgcttcctg 1380 ggaagtcact ttggcttcct ctgcaggtgg ctggggaggg atgtgggaac tgcaggttaa 1440 agccatcgct tgagccctca cggtctgggt cccacccagt tacaaagcag ctggtagcga 1500 ttaagatcac ctcttatccc tgtacttcca gagccctggc tcagccccac tctcccctcc 1560 tgcaagcccc cggactgatt agagacacag gctcctcata ccagaagcaa atacaaatgc 1620 agttcctttc tgcaaactgt gttttctaaa ttttctacaa ttcagacatt cttggatccc 1680 ctaaagagta tttgaagtga acatttttgt ctggaactaa aaccaaaatc taagaatttg 1740 cgttgtggtc tggaagtgct ctctgtgatt ttctgttgtg tttcaacctg attgcttggc 1800 aaattcatgg gagtgtcagc caacagatta tagcaattgg taacggagaa cctttgcatc 1860 ctagggtttt gattcttcaa atagaacagc ctgtaaaaag ttttcttcta ggatttcctc 1920 tctgatatgc acattaaact ctatgaaact gtaggcttaa aaacccacag tggtnnnnnn 1980 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2040 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2100 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2160 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2220 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2280 nnnnnnnnnn nnnnnnccac agtggatacc ttcaaagtga ttaaaagaag gtaacacagg 2340 aagctagtat tttctattgc tgttgttttt aataattatt tacaaaatgt tctttaatat 2400 agggcatcat aatcattgac tctgagggaa agctcaagat actgnnnnnn nnnnnnnnnn 2460 nnnnnnnncc ttagagactc caaagctgtg ataaagagnn nnnnnnnnnn nnnnnnnnnn 2520 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn ncccggcccg cctttgttcc tattcatggg 2580 tgctcaggct ctcagaatga gcactcctct tttgttttgt gtgttctgag aatatttaga 2640 tggtgtactg atgccttttc agggcaacag ggaaggtgtc agggtggcaa agtggaggct 2700 gtgctttcag caggacctgt tacccgtttt atgtcatgtt ttcctcccaa ttcacaaggc 2760 atatttttgt ttggtttcca gaaataatct tcagtggagc cctgatcttg gggtgcacca 2820 gaatggggga tttccaatgt ttctgagctg tttcccttct ggtgaacgaa ccatcctgga 2880 cgtgacaacc agaccaattt tggaaagagc tagggccatt tgctgggctg cctagtttgg 2940 aacagattaa tctgctcacc ccagcagtgg tcttgcatta agtcagagtg ctacaaaggc 3000 tttgaggtca cttcttgaaa agctgtcagc gtttccagag ccatttaagt ctctattatg 3060 tcttggtaac ttcaggtgta gcttgatgtg gtaggacatt aggtggtagg ttctctgtgt 3120 atcacaatgg catctggcat acaggcattc ttacgaaata tttcttgtgt aggtgaatta 3180 ctctgaggca gtaaaggtca ctttgcaaat gtcttaacag tcttgtaaac agagtgaaaa 3240 agcagcagca gctggcctgt ttgggagtgt actttccagg tgttcctgcc cccatttctt 3300 gggcagtatt atatttaccc ccgagcacta gttacttccc atgctcggct gacccaagga 3360 caaacacaac gctttctggg ccttctcaga caggacactg cttctagagg cagctgtcac 3420 ctcccgcgcc atctcagtac tggggtgcaa atcacatctt cggaattacc agccagagca 3480 agagaaagct ttccaccaat ccagtgcaag tctctttctg tgttaattga cagccaccct 3540 tggcatggat gaatgaatcc cagcaaccag cagactgagt gctggagtgc aggcagctca 3600 taactgtcag gcaaaagagc aagagggttt taagagagac tccagaaagt atgggatata 3660 ttaacccttg cactgtcttc tggaatagga atgacatctg tttgtattaa aacaattgtt 3720 ccgtttaagc acagtttgac agctctggag tgggagctgg agagagaact ttgacttcac 3780 tagaacctgt tggctaaggt tttaggggca caatatagaa gggtgttgga ttctagagaa 3840 gtgaaagcaa cctttttgta ctcgtgttga aaacagtgcc ctactagtat tagagtgtct 3900 cattgataga gagccaatga caaccaagtc cctactctca gagatgtttt agagttacat 3960 tgcacgaatg caaagaagca acataggaac aggtaattaa taataaagta taaactgagc 4020 agatgtcttg aaagtattct agggtatgaa aagaattcct tcaggatgct ggtaggcagc 4080 aggatctcaa agaattagtt ttgagatgag gcagaatgct ggtaaaccac acgggcagtt 4140 accttgctgt gccccctcat ttagatgtgt gccgagccct gcaagaacag aagcagctgt 4200 tccccttccc accatcatac tacaaggtta agcctaatca gaatttactg tatacctcaa 4260 aaaaattgta cagcagctac cacacacgag cacannnnnn nnnnnnnnnn nnnnnnnnnn 4320 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nngttcttgt tgctgttgct gtgtgatgct 4380 gtcagaggct tatgccctga gggagggatc aagggagtgg ctgagggtgg tcacagaaga 4440 cagattccgg ggcatgtggc ccgtacgagg atgccaaaat gccacagtca cactcacctc 4500 agaagggtgg gattggtggg ggcagagagg ggcgttgaaa tgttttgaaa attatcttca 4560 agagtatgtg aaaaaattga gaatcttgat cattctatct gaacattttc ttaggaggat 4620 tctccttttc tctttacatt cttgatcagc tcttgggtaa agacatggca gagataagag 4680 cgtgagtacc agttcctggg gtcagcaggc tctgatcctg catgcaatag agagctccag 4740 tgtattggga aggctcccaa ctcgttagga gagttgagac atcgtatctc ttgggtgaca 4800 34c gaataaattt ttcatgtcta ttaattggcc taggttgact ttaatgacat atacttttca 4860 aatgtggggc tgatggagac ctaagcagac agatctgtgg gccacccctt agccctttgc 4920 cgctctccca gggctaagga ttctgaccac agcctagtca cctgtcgcac actgctgttt 4980 ttcag 4985 <210> 3 <211> 2556 <212> DNA
<213> Homo sapiens <220>
<221> misc_feature <222> (507) ... (743) <223> n= a, t, c, or g <220>
<221> misc_feature <222> (1584) ... (1678) <223> n= a, t, c, or g <220>
<221> misc_feature <222> (2428) ... (2474) <223> n= a, t, c, or g <220>
<221> intron <222> (0) ... (0) <223> MGB-CEGP1 int 4.1 <400> 3 gtaagtatgg gccagtgcac acctgccatg ggaaccgtcg tattccacag gctgccttct 60 gtggcccagc tcagaagcac cacctcatgg cacggctgca gcagcaggga aggcagttag 120 cacgggatac cgacctctac caagtacttg ttcactgcag aagggtggtc tcccttaggg 180 aagggaaatg atattttaaa aaggaactca tcaggaggaa atgaaattca ggagtaagga 240 gtgtgaatgt tggggggcag ttctccctgt tcccacagaa taaaaccaaa tgtcctcatc 300 tggcaatcac agctctttgc caccaggtcc tgcttcccct ataaacctca tctgcctcct 360 ttccgcagac actactcccc ttgcctttgg agaacagccc aaatcctttg atgcctccag 420 gcctttccca agccctcctg ccttcctggc gtggtggact ctcactcaac cttcaatatt 480 ctgtttaact tctaataagg ataagcnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 540 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 600 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 660 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 720 nnnnnnnnnn nnnnnnnnnn nnnccatcct ctgctatcag aagcctcctg ggtgcttcag 780 acagggcagc catcttgtac tttggctccc acagcacttt cctcagctgt atagctctgg 840 gttgacttgt gtgttgatgt gtctgtctcc ccaggtatga gccccctcca agtcagggac 900 cttgcctcat ttttcctctc agtcctcccc tggtacctgc tatgggatat gctcagtaca 960 cttgtgttta atgagtgggt aaatgggtgg cctacaccat cgggccgcag ctcctgcacc 1020 acgattgtag taacaaaact ccacctggga acaggaaacc actggcaatt catggtgttc 1080 ctaaaccacg atttatgcca ggggaagcac tgaggagttc cctttaggaa ccttcccaaa 1140 gccatggaca gaagacccct gccatttggt ggggatggtg gtttatggtg agtaggagat 1200 gaggggacag tttcactggt gagggacttc tctccattgt ctccctcaca aagcagactg 1260 ccaccccaaa gctgtccaag ccaaggctgg tgccaccatc acactcaagc aacaggttct 1320 gacatgctct tagggcccct cgaagtcagg ctgtccctga gggcttccag tgagctagca 1380 gagtggagac cattttccca cctccagatc ttcggaagga agacccagac cctccaagac 1440 tcacctgcgg ggcgagaccc tcaacatttc atagtctttc agggaacagt tgctgaaggg 1500 ggcggggggg tgggcacctg taagcttgtt tttaaagatt ttaaatgtct ttaagatatc 1560 actgctcaaa taatattgtt ctgnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1620 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnncg 1680 tttgaggaat taacaaagaa aaaaactaag acctagaatc tcaccacata accagctgtt 1740 tcaatttttc catattccta tttagttgtt gttcatatgc atacacaatt tttacatagc 1800 34d tataatcaca ggacaacaca aatatgtaat tagttctttt gaattagaaa aattacaaag 1860 ggcctatgta aaatgcaaac actccaaagc atataaagaa aacatgcagt ttcccgcctc 1920 ccgtttccct tgccagaggt aaccacggtt agcagtttta tgaatagata gttttgtagt 1980 tggctttttt tctttttggc ctatcatcaa tacattcata tatagtcttg ataattacca 2040 gttactgtca cgttaattgt gtgcagaatc atcctgtgat tatccttcct tctaactaat 2100 ctagattgaa tctgatgaga gaaattctga catatatgta caaattaaat attgtctgtt 2160 ttattccagc ataaagtgct atagcatttc ccaaagcccc agtacagctg tattaatagg 2220 taaacttctc tagatagaac aaagcagtag tctagaatct cttggtataa tttcccttat 2280 ataataaaag tctctccccc aactctccca tctccctctt cctgtatgac tttgtttaaa 2340 cccatgtttc agcatttcta caatttgtat tgtaactatc tgcatacaca gacaccacag 2400 ggtctgactt ggagttatgt ctttcgtnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2460 nnnnnnnnnn nnnnaatcag aatttctctg gagcaaacac agccctgtgt ttgtggaaat 2520 ctcagtgctt tatgtattga ttcattttgc tgtcag 2556 <210> 4 <211> 716 <212> DNA
<213> Homo sapiens <220>
<221> intron <222> (0) ... (0) <223> MGB-CEGP1 int 5.1 <400> 4 gtgagtggca accccaacac tgagtgaggg tctgcaccag cctgcctgtc cctaccccta 60 ccccttaatg gtgtttagca cagatgcagg ctgtttcctg tgcatttgcc cccccagcag 120 gccctgtgct gcttcgcatg ctacagtggg agtggtctag gcctgtgggg aaggcccctc 180 tctccctgtg tgaccttggg aagcccttcc tcctctcctg gactaggctg ctcctaacgc 240 tggtattcca gagactggca caacacctcc caggaggcca gggcagcacg aagttagagc 300 tgtttataat gatgcggcac ttctggccag caggagccag ggccgtatat ttctggcggg 360 atgcctgcct tgcccttcac ggtgtgtcct tcactagctc cattttagag gtttccaggc 420 ccaaggctct ttttctcctc gactcagggg actgaagctt gcattcccta gtgtctcttt 480 ggtcagtgca atatacctcc aaaatctttt ccatgtttaa tgtttgctaa ggatctgtgg 540 ccctttaacg ggctgtgtct cccacagagc ctcattacaa cacattttta ttgcgtgaac 600 agagtcacat atctttcatt cctcttatgt ctgggatttc agcaaacaca gttgtatggg 660 gatgagcaat ctaactcatt cagtctgaga accgtgctct tttgcttctc ttgtag 716 <210> 5 <211> 2041 <212> DNA
<213> Homo sapiens <220>
<221> misc_feature <222> (559) ... (869) <223> n= a, t, c, or g <220>
<221> misc_feature <222> (888) ... (1052) <223> n= a, t, c, or g <220>
<221> misc_feature <222> (1102) ... (1380) <223> n= a, t, c, or g <220>
<221> misc_feature <222> (1393) ... (1692) 34e <223> n= a, t, c, or g <220>
<221> intron <222> (1841)...(1907) <223> FOXM1 int 3.2 <220>
<221> intron <222> (1871) ... (1936) <223> FOXM1 int 3.1 <400> 5 gtaatgtgtc ccacagcaac caaaatcaag gtcagcccag cctgacagtc tctccagtgc 60 tgtactgcaa cttgtatctg ggacagcagt taagtgcaaa ggacactaga atgataaaca 120 aatgtatctt ttagattgtg actcaatctt attgaatcca ggcaaaatca ttaagaagag 180 ctccttaact acttcatgtg ttactaccta aagtccatgg agggtcttca atgtagcact 240 caagcccact tttctgctac actcaacagc cgtcctagat gccagcagct agagtggcta 300 agtagtttta tgaaaatgtc ttgattaaaa aaaaaaatgc tgtctgtgag cctcatgacc 360 caagatgtca tctcctgtag cgtcacatag catttctagt gggcaggggt tttcctttca 420 cttcattcat ggaaagaccg agatgcctgt gagtcaacat agctcacgca gttggtcggt 480 gtcagagcca caaatgaggt cttctgacgg gtgctcaatt ccaagtcaag tgtgctttgt 540 tttcctcatg gtagaactcn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 600 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 660 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 720 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 780 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 840 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnc ctcatggtag aactatgnnn nnnnnnnnnn 900 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 960 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1020 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nncatggtag aacttttaat tttactccct 1080 tccatcagct tactttccta gnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1140 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1200 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1260 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1320 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1380 ttaatttcct agnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1440 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1500 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1560 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1620 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1680 nnnnnnnnnn nntaattccc tagtttctta atttctctga gccacctttc ttgctattga 1740 tcactacctc acagccttac tctgcttttc tagcccctga cagctatcta ggtcttttct 1800 ttatcacaat ctaaggttgg catcagtctt tattcccgta gaatagatgg gtttatggct 1860 gaaggtgacg gctctgcggt gtggagtgtc aggagagttg ccaagagggc tgcaaagaca 1920 ccagacgaag cctgtgctga gcacagtggg aggggcctga ggctggtttc cccatgtgtt 1980 tgaagggtga tgtttctgaa tctaaagtag ctgataacca gttgtcttgc tcttcttcca 2040 g 2041 <210> 6 <211> 993 <212> DNA
<213> Homo sapiens <220>
<221> intron <222> (52) ... (124) <223> FOXM1 int 4.1 <220>
<221> intron 34f <222> (110) ... (185) <223> FOXM1 int 4.2 <220>
<221> misc_feature <222> (249) ... (397) <223> n= a, t, c, or g <220>
<221> misc_feature <222> (442) ... (749) <223> n= a, t, c, or g <400> 6 gtgaatgccc tgctttcctc taaatagggc ctaagttgga ggttgtcata gccatctcaa 60 aaggaaacaa gttctgctag tgatgctttc atttgatcag gggagagtta gaagccagcc 120 acccaattag tgacttgcac aaaacccagt gaattaagta cacttgacaa ataccaaatg 180 acacattttt gtgccagacc agagcaagga gaaggctgtt ctgacccaac agaaagggct 240 ccccagggnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 300 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 360 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnntac aagaaattct gggaatgctt 420 gctctaaaaa aagcccttcc tnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 480 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 540 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 600 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 660 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 720 nnnnnnnnnn nnnnnnnnnn nnnnnnnnng cctgccttag gctggagacc agaagctgag 780 ctaccagaac gtcttttcag aaagaagtta ttttggtttt tcagagtgcc cataaggctg 840 ctggtagctg taaccattct cctgggaggg gcagttgtct ggggtgtctt ttgtcatcag 900 tcaggaataa gtgtttttcc caatccggtc aaattgacca cgttggtggt aacttcatct 960 catttctctc ccacaatgcc tggccgccac cag 993 <210> 7 <211> 602 <212> DNA
<213> Homo sapiens <220>
<221> intron <222> (0) ... (0) <223> FOXM1 int 5.1 <400> 7 gtaaggttct ttccctctgg ctcggggctt ggccttgttt tcctttcact gctcagcatg 60 gctttagtgg acagagacaa gatgtgatgt ggggaagggt ccctatggcc atgttttgtc 120 taggtgccag ccctagacac agaacaccct gagggtcagg cacacaccca cttccctccc 180 cttccatggg catcacaagg gcacactgag cagagcaggg cacagcaggg gagcatgctg 240 cagcagccac aagcgcatgg caccagcctc aggggcggca gttcgttcgc tcacttttgt 300 gcctagcttt tctttgccac gcatatagct acctgctctg gcatccccca ggggtgttga 360 ggacacgtgg gtgaagcggt agtgccactc tgccatcatg tgtctgtagg ccacccacct 420 gcccactcat cacagttttg gagactgctc gcctacgtcc atcccctcag gttggcctcc 480 tctctctggg ctgtcattaa ctcaagcaca caccaccaga gcagctggtg gggttttgcc 540 atcccctctt taccttattg tgttaacata ggtttctttc tctccccatc tgccacaagc 600 ag 602 <210> 8 <211> 4656 <212> DNA
<213> Homo sapiens <220>

34g <221> intron <222> (0) ... (0) <223> FOXM1 int 7.1 <220>
<221> misc_feature <222> (316) ... (615) <223> n= a, t, c, or g <220>
<221> misc_feature <222> (626) ... (930) <223> n= a, t, c, or g <220>
<221> misc_feature <222> (1044) ... (1259) <223> n= a, t, c, or g <220>
<221> misc_feature <222> (1452)...(1802) <223> n= a, t, c, or g <220>
<221> misc_feature <222> (2085) ... (3116) <223> n= a, t, c, or g <220>
<221> misc_feature <222> (3138) ... (3433) <223> n= a, t, c, or g <220>
<221> misc_feature <222> (3442) ... (3728) <223> n= a, t, c, or g <220>
<221> misc_feature <222> (3814) ... (4081) <223> n= a, t, c, or g <220>
<221> misc_feature <222> (4289) ... (4371) <223> n= a, t, c, or g <400> 8 gtgggtgtcc tattttcctc tgaagagaga ttctggccaa ttaagaatgt tggaccttca 60 gcttgcaaag cactctgata agtgttcctt gagagcttat aaatctagtt gggtagaaaa 120 ggcataaaaa catagggaag tgtaatagca ttagaagagc taaaaaggta tttggattac 180 aatgtaagtg gtgtcagaag gcccataaat acctgatgag cttgtaagaa ttcagacaaa 240 agtgattgtg atagatgggc taggattatt aaggaagata cacaagggag gcaggcctta 300 gaaagagatg gatttnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 360 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 420 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 480 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 540 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 600 nnnnnnnnnn nnnnngtgga tttgannnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 660 34h nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 720 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 780 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 840 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 900 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn gtagatttgg gtaagcaaac aggtgtagag 960 agagcatgct aatgggcagt gccatggagg cgggaaatgc agttcgtacc tggcagtagt 1020 aaagtgactg ggtcagacta actnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1080 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1140 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1200 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnng 1260 tctagcttga ggggaaggtg agaagggtaa attcagagcc aacttggatc agccatcaga 1320 tctgcactta acactgttaa agggttctgt gagtacgggc tgacatgtaa ccaaagtgaa 1380 aagcttcccc catccccttc agagagatga aaatagcata gagtctggag tttagagcga 1440 cttgggtttg cnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1500 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1560 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1620 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1680 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1740 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1800 nncatattac acacaaaatt ataccacaca tacataattt agcgtaaatt cattcatgtg 1860 gccgtagcat gtgccctgtt tgggttttca tgcagtgggt tttctcccct ttcctttttg 1920 gctccctctc caccctacca tcacccacat cacccctact cccaagataa ctggttgata 1980 atttatgatg ctttcttgca tattttatca atgctcttag ttatactata catgtatagc 2040 gatagccatt ttatatgtac acatacaaca cacagaacat tgatnnnnnn nnnnnnnnnn 2100 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2160 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2220 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2280 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2340 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2400 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2460 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2520 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2580 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2640 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2700 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2760 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2820 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2880 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2940 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 3000 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 3060 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnngtta 3120 tcaatttgtg agagctcnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 3180 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 3240 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 3300 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 3360 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 3420 nnnnnnnnnn nnntgtgaga gnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 3480 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 3540 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 3600 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 3660 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 3720 nnnnnnnncc ctgtgagagc tctttgttgt taaaataatc ttctttcttt tatgctgaag 3780 atatttttct acttctattg tttatctctt tacnnnnnnn nnnnnnnnnn nnnnnnnnnn 3840 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 3900 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 3960 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 4020 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 4080 ntgtttgttg tttcttaact ttgtttatgg tatctcttgc cacagtaaaa ttttaaagtt 4140 ttatgtagtc aaatgtctct cttctctttt acagtttctg ggtttccagt cttggttaag 4200 aaggtcaccc gcaccctcag attgtatatg tagtctccta gattctcttt caggatttgt 4260 atgattttaa ggttttcatt ttttttttan nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 4320 34i nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn ntaaggttct 4380 tattttcatg cattaaatct ttgtatacag tgtaagacaa gcatgcaatt ttatttcctc 4440 tcggatgaat gctattataa ttatgccact acatactaca tacccgcatc ttttaccccc 4500 agaattgaac taccaacttc aacatacatc gtattctcat atttaataga ttttaagact 4560 tcaaaacgac acaaagagga tcagaacccg tatgtgatat ttttgtgcgt cctgtctggt 4620 gaccgttggt tcaccttatc tctgtttccc tttcag 4656 <210> 9 <211> 614 <212> DNA
<213> Homo sapiens <220>
<221> intron <222> (0)...(0) <223> MGB-PRAME int 2.1 <400> 9 gtaagttcga gccctgattc ctccgcttcc ccgcagggtg accttgggct tgtgcccccg 60 gcaccacccc tgtcccgggt ccctgttttc tctctggaaa tgggttgaag accaaagaaa 120 ataatgtgcg ccacttgggt caccccgggc cgcctgcccc ggaaaattgg ccccagttga 180 ggagttgtgg ctgtaaggat gccttgaacc gaggcggcgg tgctcgtggt tggagctctc 240 cagggtgggt gcgcatttgt aatgcggtgg atgctctggg actcggcccc tctgaaggtg 300 ctgggggttg gggacggccc aggcagtggc gtaggcgtcc taggaaggcg ggagcagagg 360 cagaaatgtc gctgcaagac cgtagtcagg gtccttgacc acaggggtca cttgtgacca 420 accacatggt ctgttgttcc tcctgccccc tggttcagcc caggaaacac tggtgctcag 480 gtttggagcc agagatttgc actgaaaggg cgggattgag tcgccagttg tcagtttcct 540 cagcagtatt tgcggaggtt ttcacaggag gccgttgctt cgtaaatatt atacatgtat 600 tcttcttttt ggag 614 <210> 10 <211> 432 <212> DNA
<213> Homo sapiens <220>
<221> intron <222> (0) ... (0) <223> MGB-PRAME int 4.1 <400> 10 gtaagggtga cctagcagct tggtgtgggg ccctgggaac ctgagcagga tgcagctggg 60 gtcagggagc atggagcgcc taaggctggg ccagaggctc tgatggttgc cagcaaggaa 120 gttcagggag gccttggggc tactgcaggg gtcactcttg gaatgggctt ctggacatgg 180 ggcactgatt aaaatgcaga ggtgtctgaa ggaacatgca cctgcttcct cctggtgggg 240 tgggaattgg ggaccaggaa ggatcccagg atcctagtgg gaaagggagc agctgatgcc 300 tgaagtacga agtaaaagtg cagatctaag gtggatgtct gtttggttct tacctacatt 360 atgagactca tggtcttatt ttgagttgat cttaaagcat catctcagct aattacctgt 420 ttttccccac ag 432 <210> 11 <211> 3740 <212> DNA
<213> Homo sapiens <220>
<221> intron <222> (0) ... (0) <223> MGB-STK15 int 1.1 <220>

34j <221> misc feature <222> (84) _..(151) <223> n= a, t, c, or g <220>
<221> misc_feature <222> (321) ... (491) <223> n= a, t, c, or g <220>
<221> misc_feature <222> (537) ... (615) <223> n= a, t, c, or g <220>
<221> misc_feature <222> (853) ... (894) <223> n= a, t, c, or g <220>
<221> misc_feature <222> (1259) ... (1309) <223> n= a, t, c, or g <220>
<221> misc_feature <222> (1337) ... (2516) <223> n= a, t, c, or g <220>
<221> misc_feature <222> (2521) ... (3567) <223> n= a, t, c, or g <400> 11 gtacaagggg tttgttgagt ggtgttgaca tgcgcgggag gggtgggtgg gcttcagatt 60 ggattttgtc ctccgagatc accnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 120 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nggtaagcgt acggagaact tgcagctggg 180 gtgggtgtta cagaggaaaa gcaggagtgc ggtttaacgg gggccgcttt agatagaata 240 gcctaagaag gcccttgtcc tggctggatg agtgggtgaa ttgatgaatg agaacctcct 300 tgcagaggcc ttcccggtcc nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 360 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 420 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 480 nnnnnnnnnn ngggatgcag accggtgcat acaaatcgtc tggggacgtt aaaatgnnnn 540 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 600 nnnnnnnnnn nnnnncactg tccttaactc tcgtaatgtc tcttcctctt ccgtaacctt 660 ccttgtccct tgaattaaac gtttttcagc aacctactca gttcgtcctt cccttcatct 720 ctgcagacat gcacaggtct gagggaggaa ggaataaacc gtataaacct cctgcgctat 780 tagcctaaca gcttttctat tcaaaatagt aggacttctg gtttgaactg aatggatcct 840 gtgaaagtca tcnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnagtctc 900 cttggcgttg tctccagaat tctggattag aatcttattc cattctgctt gttattcaat 960 ttccctagaa agaaaggtag aataaattgg agcaaatgcc tgtagcttct gtcagaagaa 1020 tgttgaataa atgttgttag gcctatgtga tctcattaga ctgctactta gaattgtaag 1080 ggaagtaaag cattagagca tgtgtgaaat taaatatttg attaacacaa gtgtgcattt 1140 ccttgttgct gtttatcaac ttttacttac ccactgtttt tttataaggg ctgcagcctg 1200 tagtctgggc ctggcttcat catggaatta tttgcttaat tgtaaaatgg taatcttaan 1260 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnng gatatttgat 1320 aagaaacttc agtgaannnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1380 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1440 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1500 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1560 34k nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1620 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1680 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1740 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1800 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1860 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1920 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1980 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2040 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2100 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2160 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2220 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2280 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2340 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2400 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2460 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnggga 2520 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2580 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2640 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2700 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2760 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2820 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2880 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 2940 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 3000 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 3060 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 3120 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 3180 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 3240 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 3300 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 3360 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 3420 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 3480 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 3540 nnnnnnnnnn nnnnnnnnnn nnnnnnngca gggaaagcac atgcctgtcc ctccctcatt 3600 agcttcattt ggacaaaaca tgtaaaatcc ggtgtgttgt ggaggccttt tgattgggga 3660 actgtaacgc tgcctatcga gcaacagcac tttaagcagg tggctttgtt caaattaaag 3720 gttcttcttt ttcttttcag 3740 <210> 12 <211> 1622 <212> DNA
<213> Homo sapiens <220>
<221> intron <222> (0) ... (0) <223> MGB-STK15 int 2.1 <220>
<221> misc feature <222> (705) ... (989) <223> n= a, t, c, or g <400> 12 gtaaattgaa taatctgtaa tctcattcac atttataaac ccacatggag gttggtcttg 60 tcgggaattc tttccgcctt tactttggat ttaaatttag atcccttact gtgatcctgg 120 atatgaatta gtcacttttc tcgtgttcag taacattttg ctgcttctta gagtagcttt 180 tttgttctgc tttgtcttat aatcggctgc ttaagtttct atatccctcc actgtatgca 240 ggataatagt aataatgcat ctggcaggag ttcaaaactt ttaaaattgg ccataaatat 300 aaaataatta gaaaaaggct accttgaatt actgtatttg attctaagtt cctatgataa 360 cggccattta aaaaattgct ctatatttaa aatgtttctt tttatttgtc tttgtctgaa 420 tgcctgctgc gttgtggaca gtgtgctaat ttcaggagta actgactttg tatttggaag 480 tcttaacacc ctctctttgt agagcactca taccgttgag ctggggatgg actttgaggc 540 tttcatttct agcacttgtc cctcacttac aatgagctgt tgaagctgaa ggaaatctca 600 tccctcctac cccttttagt ttgattagct gagggtgtta gagttaactt aacaatttaa 660 ggttgtaata cagtacttac aggcgtataa ataatacatt tcaannnnnn nnnnnnnnnn 720 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 780 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 840 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 900 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 960 nnnnnnnnnn nnnnnnnnnn nnnnnnnnnt aataataata atacatttta gtagtaactt 1020 tgtgaagtgt ctacatttgt ttcctctttg tcagtttttt gctcaattcc attttgtcaa 1080 tacttggaaa atgaaacatt ggttaatcaa tagtacagta ataagcttat tgtggaaaat 1140 cttcgatata tgaaaactta gactcttcta aaacttcatg aagataatac cactgttgaa 1200 cgttttgacg tatttttttt tggtcttttt cttaaacgta tattatcaaa gaaatttcaa 1260 tggaactgag attttggcat aaagtttttg tatcatagct ttttgccaaa tagcaatgta 1320 gtgtctattt ccaaattatt gagaaatttt agaaagtgtc tccttcatta atggatattt 1380 gttaataaag catgattttt aggggtgagg aattggaggg gatagaaggt atcattcagg 1440 tattcttagc cacatactaa ctatcctctg gaggtactga ttaaaatacc ttttcacctt 1500 ccatctctta tcagtgacat tcattatttt gctatactag agaacaaact ttgtgaaatt 1560 ctcaatatat tcatcttttg ctttcatgaa tgccagaaag tttattttct cttccattct 1620 ag 1622 <210> 13 <211> 1093 <212> DNA
<213> Homo sapiens <220>
<221> intron <222> (0) ... (0) <223> MGB-STK15 int 4.1 <400> 13 gtaagctttc ttatttacaa agttctgtac tgttctacta gaatatatta tttcgttgca 60 aatttcgttg tgggaactct ggggaaaaaa atgaggcctt tatttgcatt tagaggatat 120 aaatgtttcc agatttccaa tcttaaaaaa aatggaattt tgtgtaatga ggtattttac 180 taggaactca agtgctttaa aaaatggctt tcaaatttag aaaaagcttg tatgaatctt 240 ttatagaaat gtgtggaagt tcctctctgt ccttagaaat aaccactaca tatggtttat 300 gcgtctgtac ttttttattg tacaaaagtg caagttttta aaaaatagaa tatgttgcag 360 aactatatac tcatatatga ctgagggttt tgacagtatt atagttttag ttctttattg 420 taaaggttgg ctgtaatgtc ttccccaggg cttttctaaa agcctcctct cagtctctga 480 actatctgga ctctagaatg taccgggagg agcgaggaat gaacccacag actcttttgc 540 ttttagcggt ctaacagagg ctaagagtct aaatccactg gttctcatgc cccagctagc 600 ctgtgggctc catcccgctt ccattagtaa cagtggctct gtctccacca ccagagtggt 660 tctccaccca gagagaatta gcacctctgg gactggaggg agcagctggg gttagtttga 720 aacatgcccc cagatggtct ggaagcattc ctccctctct ggtcacttat cctttttgtg 780 gtcttcagcg ttgtcatggc cctgttcctc tgagcatagt acgggcttgg gacatttccc 840 atagagtgct tcaggtctaa aacccgagac tgctccttgt cactgactct cacacctgac 900 ggcagctagg gacgtcaggg tttcatgtcg tggcagctct ttgatagtgg ttattgcctt 960 ggttcttgct gaggatgcat attgagtgaa gttggaatac gaaattattt gtagaatgtg 1020 tctgctactc attgaaaatt tgttagaaaa gctttgtttt cttcacattc taaagtgttc 1080 aaattcctcc tag 1093 <210> 14 <211> 18 <212> DNA
<213> Artificial Sequence <220>
<223> forward primer 34m <400> 14 agcgcctgtt ccgatctg 18 <210> 15 <211> 24 <212> DNA
<213> Artificial Sequence <220>
<223> reverse primer <400> 15 aaccaaagtt ctctgctgaa aacc 24 <210> 16 <211> 15 <212> DNA
<213> Artificial Sequence <220>
<223> probe <400> 16 ccctgaagca gcaac 15 <210> 17 <211> 22 <212> DNA
<213> Artificial Sequence <220>
<223> forward primer <400> 17 ctgttgctgt gtgatgctgt ca 22 <210> 18 <211> 20 <212> DNA
<213> Artificial Sequence <220>
<223> reverse primer <400> 18 cctcagccac tcccttgatc 20 <210> 19 <211> 15 <212> DNA
<213> Artificial Sequence <220>
<223> probe <400> 19 tcagggcata agcct 15 <210> 20 <211> 19 <212> DNA

34n <213> Artificial Sequence <220>
<223> forward primer <400> 20 tccccttgcc tttggagaa 19 <210> 21 <211> 19 <212> DNA
<213> Artificial Sequence <220>
<223> reverse primer <400> 21 aaaggcctgg aggcatcaa 19 <210> 22 <211> 13 <212> DNA
<213> Artificial Sequence <220>
<223> probe <400> 22 cagcccaaat cct 13 <210> 23 <211> 25 <212> DNA
<213> Artificial Sequence <220>
<223> forward primer <400> 23 cttaatggtg tttagcacag atgca 25 <210> 24 <211> 20 <212> DNA
<213> Artificial Sequence <220>
<223> reverse primer <400> 24 ccactgtagc atgcgaagca 20 <210> 25 <211> 16 <212> DNA
<213> Artificial Sequence <220>
<223> probe <400> 25 caaatgcaca ggaaac 16 <210> 26 <211> 19 <212> DNA
<213> Artificial Sequence <220>
<223> forward primer <400> 26 gctctgcggt gtggagtgt 19 <210> 27 <211> 21 <212> DNA
<213> Artificial Sequence <220>
<223> reverse primer <400> 27 cacaggcttc gtctggtgtc t 21 <210> 28 <211> 24 <212> DNA
<213> Artificial Sequence <220>
<223> probe <400> 28 tgcagccctc ttggcaactc tcct 24 <210> 29 <211> 23 <212> DNA
<213> Artificial Sequence <220>
<223> forward primer <400> 29 aaaatgctgt ctgtgagcct cat 23 <210> 30 <211> 21 <212> DNA
<213> Artificial Sequence <220>
<223> reverse primer <400> 30 aacccctgcc cactagaaat g 21 <210> 31 <211> 30 <212> DNA

34p <213> Artificial Sequence <220>
<223> probe <400> 31 acccaagatg tcatctcctg tagcgtcaca 30 <210> 32 <211> 25 <212> DNA
<213> Artificial Sequence <220>
<223> forward primer <400> 32 aatagatggg tttatggctg aaggt 25 <210> 33 <211> 23 <212> DNA
<213> Artificial Sequence <220>
<223> reverse primer <400> 33 ctcttggcaa ctctcctgac act 23 <210> 34 <211> 13 <212> DNA
<213> Artificial Sequence <220>
<223> probe <400> 34 ccgcagagcc gtc 13 <210> 35 <211> 25 <212> DNA
<213> Artificial Sequence <220>
<223> forward primer <400> 35 ccatctcaaa aggaaacaag ttctg 25 <210> 36 <211> 21 <212> DNA
<213> Artificial Sequence <220>
<223> reverse primer 34q <400> 36 gggtggctgg cttctaactc t 21 <210> 37 <211> 24 <212> DNA
<213> Artificial Sequence <220>
<223> probe <400> 37 ccctgatcaa atgaaagcat cact 24 <210> 38 <211> 20 <212> DNA
<213> Artificial Sequence <220>
<223> forward primer <400> 38 agaagccagc cacccaatta 20 <210> 39 <211> 26 <212> DNA
<213> Artificial Sequence <220>
<223> reverse primer <400> 39 tgtgtcattt ggtatttgtc aagtgt 26 <210> 40 <211> 26 <212> DNA
<213> Artificial Sequence <220>
<223> probe <400> 40 tgacttgcac aaaacccagt gaatta 26 <210> 41 <211> 24 <212> DNA
<213> Artificial Sequence <220>
<223> forward primer <400> 41 tggacagaga caagatgtga tgtg 24 <210> 42 <211> 22 <212> DNA

34r <213> Artificial Sequence <220>
<223> reverse primer <400> 42 gctggcacct agacaaaaca tg 22 <210> 43 <211> 15 <212> DNA
<213> Artificial Sequence <220>
<223> probe <400> 43 ccatagggac ccttc 15 <210> 44 <211> 25 <212> DNA
<213> Artificial Sequence <220>
<223> forward primer <400> 44 ggtgtcctat tttcctctga agaga 25 <210> 45 <211> 21 <212> DNA
<213> Artificial Sequence <220>
<223> reverse primer <400> 45 tgcaagctga aggtccaaca t 21 <210> 46 <211> 15 <212> DNA
<213> Artificial Sequence <220>
<223> probe <400> 46 ttctggccaa ttaag 15 <210> 47 <211> 21 <212> DNA
<213> Artificial Sequence <220>
<223> forward primer 34s <400> 47 tcattcatgt ggccgtagca t 21 <210> 48 <211> 19 <212> DNA
<213> Artificial Sequence <220>
<223> reverse primer <400> 48 ggtggagagg gagccaaaa 19 <210> 49 <211> 16 <212> DNA
<213> Artificial Sequence <220>
<223> probe <400> 49 cctgtttggg ttttca 16 <210> 50 <211> 23 <212> DNA
<213> Artificial Sequence <220>
<223> forward primer <400> 50 agaggatcag aacccgtatg tga 23 <210> 51 <211> 24 <212> DNA
<213> Artificial Sequence <220>
<223> reverse primer <400> 51 gggaaacaga gataaggtga acca 24 <210> 52 <211> 15 <212> DNA
<213> Artificial Sequence <220>
<223> probe <400> 52 tgtgcgtcct gtctg 15 <210> 53 <211> 19 <212> DNA

34t <213> Artificial Sequence <220>
<223> forward primer <400> 53 gggtgacctt gggcttgtg 19 <210> 54 <211> 23 <212> DNA
<213> Artificial Sequence <220>
<223> reverse primer <400> 54 cttcaaccca tttccagaga gaa 23 <210> 55 <211> 14 <212> DNA
<213> Artificial Sequence <220>
<223> probe <400> 55 cccgggtccc tgtt 14 <210> 56 <211> 21 <212> DNA
<213> Artificial Sequence <220>
<223> forward primer <400> 56 agggtgacct agcagcttgg t 21 <210> 57 <211> 18 <212> DNA
<213> Artificial Sequence <220>
<223> reverse primer <400> 57 gcctctggcc cagcctta 18 <210> 58 <211> 16 <212> DNA
<213> Artificial Sequence <220>
<223> probe 34u <400> 58 tccctgaccc cagctg 16 <210> 59 <211> 25 <212> DNA
<213> Artificial Sequence <220>
<223> forward primer <400> 59 cgtaatgtct cttcctcttc cgtaa 25 <210> 60 <211> 24 <212> DNA
<213> Artificial Sequence <220>
<223> reverse primer <400> 60 acgaactgag taggttgctg aaaa 24 <210> 61 <211> 16 <212> DNA
<213> Artificial Sequence <220>
<223> probe <400> 61 tcaagggaca aggaag 16 <210> 62 <211> 26 <212> DNA
<213> Artificial Sequence <220>
<223> forward primer <400> 62 cattcacatt tataaaccca catgga 26 <210> 63 <211> 23 <212> DNA
<213> Artificial Sequence <220>
<223> reverse primer <400> 63 aatccaaagt aaaggcggaa aga 23 <210> 64 <211> 16 <212> DNA

34v <213> Artificial Sequence <220>
<223> probe <400> 64 tggtcttgtc gggaat 16 <210> 65 <211> 20 <212> DNA
<213> Artificial Sequence <220>
<223> forward primer <400> 65 gcgaggaatg aacccacaga 20 <210> 66 <211> 25 <212> DNA
<213> Artificial Sequence <220>
<223> reverse primer <400> 66 gcatgagaac cagtggattt agact 25 <210> 67 <211> 16 <212> DNA
<213> Artificial Sequence <220>
<223> probe <400> 67 cgctaaaagc aaaaga 16 34w

Claims (11)

Claims:
1. A method for predicting the likelihood of survival, disease recurrence, or response to treatment of a human subject with cancer, comprising:
(a) hybridizing a polynucleotide that is complementary to an intronic RNA
sequence of a human target gene to intronic RNA from a tissue sample obtained from the human subject with cancer, or a nucleic acid produced thereform, to form a complex;
(b) quantifying the complex to determine a level of the intronic RNA;
(c) normalizing the level of the intronic RNA relative to the expression level of one or more reference genes in the tissue sample to determine a normalized level of the intronic RNA;
(d) comparing the normalized level of the intronic RNA to data based on a normalized level of the intronic RNA in cancer tissue samples obtained from patients of known clinical outcome; and (e) predicting the likelihood of survival, disease recurrence, or response to treatment for the human subject with cancer based on results obtained from step (d);
wherein the level of the intronic RNA correlates with the level of an exonic mRNA
within the human target gene.
2. The method of claim 1, wherein the tissue sample is a resected tumor specimen or a tumor biopsy.
3. The method of claim 1 or 2, wherein the tissue sample is a fixed, wax-embedded tissue specimen.
4. The method of any one of claims 1 to 3, wherein the cancer is breast cancer.
5. The method of any one of claims 1 to 4, wherein the polynucleotide is a primer and the complex is quantitatively detected using quantitative PCR.
6. The method of any one of claims 1 to 5, wherein the polynucleotide is an oligonucleotide.
7. A method for predicting the likelihood of survival, disease recurrence, or response to treatment of a human subject with cancer, comprising:
(a) hybridizing a polynucleotide that is immobilized on a solid support and that is complementary to an intronic RNA sequence of a human target gene to intronic RNA
from a tissue sample obtained from the human subject with cancer, or a nucleic acid produced thereform, to form a complex;
(b) quantifying the complex to determine a level of the intronic RNA;
(c) normalizing the level of the intronic RNA relative to the expression level of one or more reference genes in the tissue sample to determine a normalized level of the intronic RNA;
(d) comparing the normalized level of the intronic RNA to data based on a normalized level of the intronic RNA in cancer tissue samples obtained from patients of known clinical outcome; and (e) predicting the likelihood of survival, disease recurrence, or response to treatment for the human subject with cancer based on results obtained from step (d);
wherein the level of the intronic RNA correlates with the level of an exonic mRNA

within the human target gene.
8. The method of claim 7, wherein the tissue sample is a resected tumor specimen or a tumor biopsy.
9. The method of claim 7 or 8, wherein the tissue sample is a fixed, wax-embedded tissue specimen.
10. The method of any one of claims 7 to 9, wherein the cancer is breast cancer.
11. The method of any one of claims 7 to 10, wherein the polynucleotide is an oligonucleotide.
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Families Citing this family (52)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DK2799555T3 (en) * 2002-03-13 2017-05-22 Genomic Health Inc Gene Expression Profiling in Tumor Tissue Biopsies
AU2003295598B2 (en) 2002-11-15 2009-12-24 Genomic Health, Inc. Gene expression profiling of EGFR positive cancer
US20040231909A1 (en) 2003-01-15 2004-11-25 Tai-Yang Luh Motorized vehicle having forward and backward differential structure
PT1597391E (en) * 2003-02-20 2008-12-19 Genomic Health Inc Use of intronic rna to measure gene expression
CA2527285A1 (en) * 2003-05-28 2004-12-23 Genomic Health, Inc. Gene expression markers for predicting response to chemotherapy
EP3470535B1 (en) * 2003-06-24 2020-04-01 Genomic Health, Inc. Prediction of likelihood of cancer recurrence
EP2947160B1 (en) 2004-04-09 2017-07-12 Genomic Health, Inc. Gene expression markers for predicting response to chemotherapy
AU2012200431B2 (en) * 2004-04-09 2013-06-27 Fondazione Irccs Istituto Nazionale Dei Tumori Gene expression markers for predicting response to chemotherapy
AU2006270063A1 (en) * 2005-07-15 2007-01-25 Applied Biosystems, Llc. Methods for RNA profiling
WO2007025044A2 (en) * 2005-08-24 2007-03-01 Bristol-Myers Squibb Company Biomarkers and methods for determining sensitivity to epidermal growth factor receptor modulators
BRPI0706511A2 (en) 2006-01-11 2011-03-29 Genomic Health Inc gene expression markers for colorectal cancer prognosis
US7888019B2 (en) 2006-03-31 2011-02-15 Genomic Health, Inc. Genes involved estrogen metabolism
CA2651995C (en) 2006-05-18 2017-04-25 Molecular Profiling Institute, Inc. System and method for determining individualized medical intervention for a disease state
US8768629B2 (en) * 2009-02-11 2014-07-01 Caris Mpi, Inc. Molecular profiling of tumors
US8338109B2 (en) 2006-11-02 2012-12-25 Mayo Foundation For Medical Education And Research Predicting cancer outcome
WO2009026128A2 (en) * 2007-08-16 2009-02-26 Genomic Health, Inc. Gene expression markers of recurrence risk in cancer patients after chemotherapy
DK2288727T3 (en) * 2008-05-14 2013-10-21 Genomic Health Inc Predictors of patient response to treatment with EGF receptor inhibitors
AU2009253675A1 (en) 2008-05-28 2009-12-03 Genomedx Biosciences, Inc. Systems and methods for expression-based discrimination of distinct clinical disease states in prostate cancer
US10407731B2 (en) 2008-05-30 2019-09-10 Mayo Foundation For Medical Education And Research Biomarker panels for predicting prostate cancer outcomes
US10359425B2 (en) * 2008-09-09 2019-07-23 Somalogic, Inc. Lung cancer biomarkers and uses thereof
US20100221752A2 (en) * 2008-10-06 2010-09-02 Somalogic, Inc. Ovarian Cancer Biomarkers and Uses Thereof
CN102232117A (en) * 2008-10-14 2011-11-02 卡里斯Mpi公司 Gene and gene expressed protein targets depicting biomarker patterns and signature sets by tumor type
WO2010056337A2 (en) * 2008-11-12 2010-05-20 Caris Mpi, Inc. Methods and systems of using exosomes for determining phenotypes
US10236078B2 (en) 2008-11-17 2019-03-19 Veracyte, Inc. Methods for processing or analyzing a sample of thyroid tissue
US9495515B1 (en) 2009-12-09 2016-11-15 Veracyte, Inc. Algorithms for disease diagnostics
US20120041274A1 (en) 2010-01-07 2012-02-16 Myriad Genetics, Incorporated Cancer biomarkers
US9074258B2 (en) 2009-03-04 2015-07-07 Genomedx Biosciences Inc. Compositions and methods for classifying thyroid nodule disease
SG175832A1 (en) * 2009-05-01 2011-12-29 Genomic Health Inc Gene expression profile algorithm and test for likelihood of recurrence of colorectal cancer and response to chemotherapy
EP2427575B1 (en) 2009-05-07 2018-01-24 Veracyte, Inc. Methods for diagnosis of thyroid conditions
US10446272B2 (en) 2009-12-09 2019-10-15 Veracyte, Inc. Methods and compositions for classification of samples
JP5808349B2 (en) 2010-03-01 2015-11-10 カリス ライフ サイエンシズ スウィッツァーランド ホールディングスゲーエムベーハー Biomarkers for theranosis
KR20130043104A (en) 2010-04-06 2013-04-29 카리스 라이프 사이언스 룩셈부르크 홀딩스 Circulating biomarkers for disease
EP3812469A1 (en) 2010-07-07 2021-04-28 Myriad Genetics, Inc. Gene signatures for cancer prognosis
CN102985819B (en) 2010-07-09 2015-04-15 私募蛋白质体公司 Lung cancer biomarkers and uses thereof
DE102010033575B4 (en) 2010-08-02 2016-01-14 Eberhard-Karls-Universität Tübingen Universitätsklinikum ASPP2 splice variant
AU2011289284B2 (en) 2010-08-13 2015-04-09 Somalogic Operating Co., Inc. Pancreatic cancer biomarkers and uses thereof
WO2012030840A2 (en) 2010-08-30 2012-03-08 Myriad Genetics, Inc. Gene signatures for cancer diagnosis and prognosis
WO2012174203A2 (en) * 2011-06-14 2012-12-20 Anthony Albino Methods and kits for the detection and treatment of recurring prostate cancer
WO2013010074A1 (en) 2011-07-13 2013-01-17 Primeradx, Inc. Multimodal methods for simultaneous detection and quantification of multiple nucleic acids in a sample
GB201114919D0 (en) * 2011-08-30 2011-10-12 Glaxosmithkline Biolog Sa Method
EP2791359B1 (en) 2011-12-13 2020-01-15 Decipher Biosciences, Inc. Cancer diagnostics using non-coding transcripts
EP3435084B1 (en) 2012-08-16 2023-02-22 Decipher Biosciences, Inc. Prostate cancer prognostics using biomarkers
EP4190918A1 (en) 2012-11-16 2023-06-07 Myriad Genetics, Inc. Gene signatures for cancer prognosis
WO2014186036A1 (en) 2013-03-14 2014-11-20 Allegro Diagnostics Corp. Methods for evaluating copd status
US11976329B2 (en) 2013-03-15 2024-05-07 Veracyte, Inc. Methods and systems for detecting usual interstitial pneumonia
EP3143160B1 (en) 2014-05-13 2019-11-06 Myriad Genetics, Inc. Gene signatures for cancer prognosis
EP3770274A1 (en) 2014-11-05 2021-01-27 Veracyte, Inc. Systems and methods of diagnosing idiopathic pulmonary fibrosis on transbronchial biopsies using machine learning and high dimensional transcriptional data
CN110506127B (en) 2016-08-24 2024-01-12 维拉科特Sd公司 Use of genomic tags to predict responsiveness of prostate cancer patients to post-operative radiation therapy
CA3050984A1 (en) 2017-01-20 2018-07-26 Decipher Biosciences, Inc. Molecular subtyping, prognosis, and treatment of bladder cancer
AU2018230784A1 (en) 2017-03-09 2019-10-10 Decipher Biosciences, Inc. Subtyping prostate cancer to predict response to hormone therapy
EP3622087A4 (en) 2017-05-12 2021-06-16 Decipher Biosciences, Inc. Genetic signatures to predict prostate cancer metastasis and identify tumor agressiveness
US11217329B1 (en) 2017-06-23 2022-01-04 Veracyte, Inc. Methods and systems for determining biological sample integrity

Family Cites Families (73)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
USRE35491E (en) 1982-11-04 1997-04-08 The Regents Of The University Of California Methods and compositions for detecting human tumors
US4699877A (en) 1982-11-04 1987-10-13 The Regents Of The University Of California Methods and compositions for detecting human tumors
IE56509B1 (en) 1982-11-04 1991-08-28 Univ California Methods for oncogenic detection
US7838216B1 (en) 1986-03-05 2010-11-23 The United States Of America, As Represented By The Department Of Health And Human Services Human gene related to but distinct from EGF receptor gene
US5015568A (en) 1986-07-09 1991-05-14 The Wistar Institute Diagnostic methods for detecting lymphomas in humans
US5202429A (en) 1986-07-09 1993-04-13 The Wistar Institute DNA molecules having human BCL-2 gene sequences
US4968603A (en) 1986-12-31 1990-11-06 The Regents Of The University Of California Determination of status in neoplastic disease
US5831066A (en) 1988-12-22 1998-11-03 The Trustees Of The University Of Pennsylvania Regulation of bcl-2 gene expression
US6582908B2 (en) * 1990-12-06 2003-06-24 Affymetrix, Inc. Oligonucleotides
US5858678A (en) 1994-08-02 1999-01-12 St. Louis University Apoptosis-regulating proteins
US5830753A (en) 1994-09-30 1998-11-03 Ludwig Institute For Cancer Research Isolated nucleic acid molecules coding for tumor rejection antigen precursor dage and uses thereof.
US6416635B1 (en) * 1995-07-24 2002-07-09 Tokyo Electron Limited Method and apparatus for sputter coating with variable target to substrate spacing
JP3944241B2 (en) 1995-12-18 2007-07-11 スージェン・インコーポレーテッド Diagnosis and treatment of AUR-1 and / or AUR-2 related diseases
US6716575B2 (en) 1995-12-18 2004-04-06 Sugen, Inc. Diagnosis and treatment of AUR1 and/or AUR2 related disorders
US5670325A (en) 1996-08-14 1997-09-23 Exact Laboratories, Inc. Method for the detection of clonal populations of transformed cells in a genomically heterogeneous cellular sample
US5741650A (en) 1996-01-30 1998-04-21 Exact Laboratories, Inc. Methods for detecting colon cancer from stool samples
US5821082A (en) 1996-05-23 1998-10-13 St. Louis University Health Sciences Center Anti-proliferation domain of a human Bcl-2 and DNA encoding the same
US6143529A (en) 1996-08-14 2000-11-07 Exact Laboratories, Inc. Methods for improving sensitivity and specificity of screening assays
US5952178A (en) 1996-08-14 1999-09-14 Exact Laboratories Methods for disease diagnosis from stool samples
US6100029A (en) 1996-08-14 2000-08-08 Exact Laboratories, Inc. Methods for the detection of chromosomal aberrations
US6146828A (en) 1996-08-14 2000-11-14 Exact Laboratories, Inc. Methods for detecting differences in RNA expression levels and uses therefor
US6203993B1 (en) 1996-08-14 2001-03-20 Exact Science Corp. Methods for the detection of nucleic acids
US5928870A (en) 1997-06-16 1999-07-27 Exact Laboratories, Inc. Methods for the detection of loss of heterozygosity
US6020137A (en) 1996-08-14 2000-02-01 Exact Laboratories, Inc. Methods for the detection of loss of heterozygosity
US5861278A (en) 1996-11-01 1999-01-19 Genetics Institute, Inc. HNF3δ compositions
AU736587B2 (en) 1996-11-20 2001-08-02 Yale University Survivin, a protein that inhibits cellular apoptosis, and its modulation
US5830665A (en) 1997-03-03 1998-11-03 Exact Laboratories, Inc. Contiguous genomic sequence scanning
US6033893A (en) 1997-06-26 2000-03-07 Incyte Pharmaceuticals, Inc. Human cathepsin
WO1999002714A1 (en) 1997-07-07 1999-01-21 Abbott Laboratories Reagents and methods useful for detecting diseases of the breast
US6020135A (en) 1998-03-27 2000-02-01 Affymetrix, Inc. P53-regulated genes
WO1999064626A2 (en) 1998-06-06 1999-12-16 Genostic Pharma Limited Probes used for genetic profiling
US6696558B2 (en) 1998-09-09 2004-02-24 The Burnham Institute Bag proteins and nucleic acid molecules encoding them
WO2000050595A2 (en) 1999-02-25 2000-08-31 Ivan Gout Nucleic acid molecules associated with melanoma and thyroid tumors
AU3395900A (en) 1999-03-12 2000-10-04 Human Genome Sciences, Inc. Human lung cancer associated gene sequences and polypeptides
US20020039764A1 (en) 1999-03-12 2002-04-04 Rosen Craig A. Nucleic, acids, proteins, and antibodies
US6692916B2 (en) 1999-06-28 2004-02-17 Source Precision Medicine, Inc. Systems and methods for characterizing a biological condition or agent using precision gene expression profiles
US6960439B2 (en) 1999-06-28 2005-11-01 Source Precision Medicine, Inc. Identification, monitoring and treatment of disease and characterization of biological condition using gene expression profiles
US6326148B1 (en) 1999-07-12 2001-12-04 The Regents Of The University Of California Detection of copy number changes in colon cancer
US6710170B2 (en) 1999-09-10 2004-03-23 Corixa Corporation Compositions and methods for the therapy and diagnosis of ovarian cancer
US6271002B1 (en) 1999-10-04 2001-08-07 Rosetta Inpharmatics, Inc. RNA amplification method
WO2001025250A1 (en) 1999-10-06 2001-04-12 The Regents Of The University Of California Differentially expressed genes associated with her-2/neu overexpression
CA2391455A1 (en) 1999-12-01 2001-06-07 Genentech, Inc. Secreted and transmembrane polypeptides and nucleic acids encoding the same
US6750013B2 (en) 1999-12-02 2004-06-15 Protein Design Labs, Inc. Methods for detection and diagnosing of breast cancer
US6248535B1 (en) * 1999-12-20 2001-06-19 University Of Southern California Method for isolation of RNA from formalin-fixed paraffin-embedded tissue specimens
AU2001232485A1 (en) 2000-01-13 2001-07-24 Amsterdam Support Diagnostics B.V. A universal nucleic acid amplification system for nucleic acids in a sample
US6322986B1 (en) 2000-01-18 2001-11-27 Albany Medical College Method for colorectal cancer prognosis and treatment selection
CA2398107C (en) 2000-01-28 2013-11-19 Althea Technologies, Inc. Methods for analysis of gene expression
WO2001055309A2 (en) 2000-01-31 2001-08-02 Human Genome Sciences, Inc. Nucleic acids, proteins, and antibodies
WO2001070979A2 (en) 2000-03-21 2001-09-27 Millennium Pharmaceuticals, Inc. Genes, compositions, kits, and method for identification, assessment, prevention and therapy of ovarian cancer
AU2001249600A1 (en) 2000-03-31 2001-10-15 University Of Louisville Research Foundation, Inc. Microarrays to screen regulatory genes
WO2002000677A1 (en) 2000-06-07 2002-01-03 Human Genome Sciences, Inc. Nucleic acids, proteins, and antibodies
US20030165952A1 (en) 2000-07-21 2003-09-04 Sten Linnarsson Method and an alggorithm for mrna expression analysis
AU2001278070A1 (en) 2000-07-26 2002-02-05 Applied Genomics, Inc. Basal cell markers in breast cancer and uses thereof
WO2002008260A2 (en) 2000-07-26 2002-01-31 Stanford University Bstp-ecg1 protein and related reagents and methods of use thereof
WO2002008282A2 (en) 2000-07-26 2002-01-31 Stanford University Bstp-ras/rerg protein and related reagents and methods of use thereof
US7795232B1 (en) 2000-08-25 2010-09-14 Genta Incorporated Methods of treatment of a bcl-2 disorder using bcl-2 antisense oligomers
US6582919B2 (en) 2001-06-11 2003-06-24 Response Genetics, Inc. Method of determining epidermal growth factor receptor and HER2-neu gene expression and correlation of levels thereof with survival rates
US6602670B2 (en) 2000-12-01 2003-08-05 Response Genetics, Inc. Method of determining a chemotherapeutic regimen based on ERCC1 expression
US20030143539A1 (en) 2000-12-08 2003-07-31 Francois Bertucci Gene expression profiling of primary breast carcinomas using arrays of candidate genes
WO2002068579A2 (en) 2001-01-10 2002-09-06 Pe Corporation (Ny) Kits, such as nucleic acid arrays, comprising a majority of human exons or transcripts, for detecting expression and other uses thereof
AU2002246970B2 (en) 2001-01-12 2007-06-14 Yale University Detection of survivin in the biological fluids of cancer patients
US7776518B2 (en) 2001-01-12 2010-08-17 Yale University Detection of survivin in the biological fluids of cancer patients
EP1425302A2 (en) 2001-01-24 2004-06-09 Protein Design Labs Methods of diagnosis of breast cancer, compositions and methods of screening for modulators of breast cancer
IL157872A0 (en) 2001-03-12 2004-03-28 Monogen Inc A panel for detecting a generic disease state containing a plurality of probes and using cell-based diagnosis
DK1410011T3 (en) 2001-06-18 2011-07-18 Netherlands Cancer Inst Diagnosis and prognosis of breast cancer patients
WO2003011897A1 (en) 2001-07-27 2003-02-13 The Regents Of The University Of California Modulation of heregulin and her3 interaction
US7026123B1 (en) * 2001-08-29 2006-04-11 Pioneer Hi-Bred International, Inc. UTR tag assay for gene function discovery
WO2003029273A2 (en) 2001-09-28 2003-04-10 Whitehead Institute For Biomedical Research Classification of lung carcinomas using gene expression analysis
JP5236856B2 (en) 2001-11-09 2013-07-17 ライフ テクノロジーズ コーポレーション Identification, observation and treatment of diseases and identification of biological states using gene expression profiles
US20030198972A1 (en) 2001-12-21 2003-10-23 Erlander Mark G. Grading of breast cancer
CA2480635A1 (en) 2002-03-28 2003-10-09 Allen D. Delaney Cancer associated protein kinases and their uses
EP1365034A3 (en) 2002-05-21 2004-02-18 Bayer HealthCare AG Methods and compositions for the prediction, diagnosis, prognosis, prevention and treatment of malignant neoplasia
PT1597391E (en) * 2003-02-20 2008-12-19 Genomic Health Inc Use of intronic rna to measure gene expression

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AU2004213871B2 (en) 2009-01-29
DK1597391T3 (en) 2009-01-12
JP2007075127A (en) 2007-03-29
WO2004074518A1 (en) 2004-09-02
US20040191817A1 (en) 2004-09-30
JP2006518602A (en) 2006-08-17
AU2004213871B9 (en) 2009-09-03
US7767391B2 (en) 2010-08-03
ES2314378T3 (en) 2009-03-16
AU2004213871A1 (en) 2004-09-02
ATE412779T1 (en) 2008-11-15
DE602004017426D1 (en) 2008-12-11
EP1597391A1 (en) 2005-11-23

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